System and Method for Proximity-Based Analysis of Multiple Agricultural Entities

ABSTRACT

A system for proximity-based analysis of multiple entities includes a first communication device associated with a first entity and an additional communication device associated with an additional entity, wherein the first communication device and the additional communication device are communicatively couplable. The system includes one or more processors communicatively coupled to at least one of the first communication device or the at least an additional communication device. The one or more processors are configured to: identify a spatial relationship between the first entity and the additional entity based on one or more signals from the first communication device or the additional communication device, identify an operation unit defined by an association between the first entity and the additional entity based on the spatial relationship between the first entity and the at least the additional entity, and report one or more characteristics of the operation unit.

CROSS-REFERENCE TO RELATED APPLICATION

The present application is related to and claims benefit of the earliestavailable effective filing date from the following applications: Thepresent application constitutes continuation application of U.S. patentapplication Ser. No. 16/012,669, filed Jun. 19, 2018, which constitutesa continuation-in-part patent application of U.S. patent applicationSer. No. 15/215,315, filed Jul. 20, 2016, which is a regular(non-provisional) patent application of U.S. Provisional Application No.62/194,521, filed Jul. 20, 2015, and U.S. Provisional Application No.62/196,584, filed Jul. 24, 2015, whereby all of the above-listed patentapplications are incorporated by reference herein in their entirety

TECHNICAL FIELD

The present invention generally relates to proximity sensing of multipleagricultural devices, and, more particularly, to proximity-basedanalysis of multiple agricultural devices.

BACKGROUND

Tracking resources and cost is critical in both agricultural productionand non-agricultural production settings. In the case of farmproduction, it is currently difficult to track inventory, associatedinput costs, and machine use from one area of a farm down to an areawhere the given entity is used or consumed. The tracking of resourcesand associated costs are currently performed manually, resulting in atedious and inefficient process. Therefore, it would be desirable toprovide a method and system that cure the shortfalls of the previousapproaches identified above.

SUMMARY

A system is disclosed, in accordance with one or more embodiments of thepresent disclosure. In one embodiment, the system includes a firstcommunication device associated with a first entity. In anotherembodiment, the system includes an additional communication deviceassociated with an additional entity, wherein the first communicationdevice and the additional communication device are communicativelycouplable. In another embodiment, the system includes a database. Inanother embodiment, the system includes one or more processorscommunicatively coupled to at least one of the first communicationdevice or the at least an additional communication device. In anotherembodiment, the one or more processors are configured to: identify aspatial relationship between the first entity and the additional entitybased on one or more signals from the first communication device or oneor more signals from the additional communication device; identify anoperation unit defined by an association between the first entity andthe additional entity based on the spatial relationship between thefirst entity and the additional entity; define a geo-fenced area;determine whether the operation unit is positioned within the definedgeo-fenced area; determine one or more location-based characteristics ofthe operation unit based on the determination of the operation unitwithin the defined geo-fenced area and one or more characteristics ofthe association between the first entity and the additional entity;store the one or more characteristics of the operation unit in thedatabase; and report the one or more characteristics of the operationunit via a user interface.

A system is disclosed, in accordance with one or more embodiments of thepresent disclosure. In one embodiment, the system includes a userinterface. In another embodiment, the system includes a server. Inanother embodiment, the server includes a memory and one or moreprocessors. In another embodiment, the one or more processors areconfigured to: receive one or more signals from a first communicationdevice associated with a first entity; receive one or more signals fromat least an additional communication device associated with anadditional entity; identify a spatial relationship between the firstentity and the additional entity based on one or more signals from thefirst communication device or one or more signals from the additionalcommunication device; identify an operation unit defined by anassociation between the first entity and the additional entity based onthe spatial relationship between the first entity and the additionalentity; define a geo-fenced area; determine whether the operation unitis positioned within the defined geo-fenced area; determine one or morelocation-based characteristics of the operation unit based on thedetermination of the operation unit within the defined geo-fenced areaand one or more characteristics of the association between the firstentity and the additional entity; store the one or more characteristicsof the operation unit in memory; and report the one or morecharacteristics of the operation unit via the user interface.

A method is disclosed, in accordance with one or more embodiments of thepresent disclosure. In one embodiment, the method includes associating afirst communication device with a first entity. In another embodiment,the method includes associating an additional communication device withan additional entity, wherein the first communication device and theadditional communication device are communicatively couplable. Inanother embodiment, the method includes identifying a spatialrelationship between the first entity and the additional entity based onone or more signals from the first communication device or one or moresignals from the additional communication device. In another embodiment,the method includes identifying an operation unit defined by anassociation between the first entity and the additional entity based onthe spatial relationship between the first entity and the additionalentity. In another embodiment, the method includes defining a geo-fencedarea. In another embodiment, the method includes determining whether theoperation unit is positioned within the defined geo-fenced area. Inanother embodiment, the method includes determining one or morelocation-based characteristics of the operation unit based on thedetermination of the operation unit within the defined geo-fenced areaand one or more characteristics of the association between the firstentity and the additional entity. In another embodiment, the methodincludes storing the one or more characteristics of the operation unitin a database. In another embodiment, the method includes reporting theone or more characteristics of the operation unit via a user interface.

It is to be understood that both the foregoing general description andthe following detailed description are exemplary and explanatory onlyand are not necessarily restrictive of the invention as claimed. Theaccompanying drawings, which are incorporated in and constitute a partof the specification, illustrate embodiments of the invention andtogether with the general description, serve to explain the principlesof the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

The numerous advantages of the disclosure may be better understood bythose skilled in the art by reference to the accompanying figures inwhich:

FIG. 1 depicts a graphical display of a geo-fenced area, in accordancewith one or more embodiments of the present disclosure.

FIG. 2 illustrates a system determining spatial relationships betweenentities, in accordance with one or more embodiments of the presentdisclosure;

FIG. 3 illustrates a simplified block diagram of a beacon fordetermining spatial relationships between entities, in accordance withone or more embodiments of the present disclosure;

FIG. 4 illustrates a simplified block diagram of a scanner fordetermining spatial relationships between entities, in accordance withone or more embodiments of the present disclosure;

FIGS. 5A-5E illustrate a system for determining spatial relationshipsbetween entities, in accordance with one or more embodiments of thepresent disclosure;

FIGS. 6A-6B depict a portion of a geo-fenced field in which costallocations have been broken down into smaller field subsections, inaccordance with one or more embodiments of the present disclosure;

FIGS. 7A-7E illustrate a graphical display screen depicting a map and acorresponding timeline, in accordance with one or more embodiments ofthe present disclosure;

FIG. 8 illustrates a flowchart of a method for determining spatialrelationships between entities, in accordance with one or moreembodiments of the present disclosure; and

FIGS. 9-19 illustrate a graphical user interfaces for providingproximity-based analysis, in accordance with one or more embodiments ofthe present disclosure.

DETAILED DESCRIPTION

Reference will now be made in detail to the subject matter disclosed,which is illustrated in the accompanying drawings. Referring generallyto FIGS. 1 through 6, a system and method for proximity-based analysisof multiple agricultural entities are illustrated, in accordance withone or more embodiments of the present disclosure.

It is to be understood that the present disclosure is to be regarded asillustrative of the various embodiments of the present invention, and isnot limited to the following description or the accompanying drawings.Also, it is to be understood that the terminology used herein is for thepurpose of description only, and should not be regarded as limiting.

Embodiments of the present disclosure are directed to spatialrelationships between many different entities and communication devices,including people, equipment, and places. As such, it will beadvantageous to define various terms prior to describing embodiments ofthe present disclosure.

The term “entity,” as it applies to the present disclosure, refers toany person and/or object which may be tracked and identified forproximity sensing throughout the present disclosure. Entities mayinclude any person or object intended to participate in the proximitysensing of the present disclosure including, but not limited to, people,vehicles, tractors, combines, trailers, tillage equipment, fuel tanks,and the like.

The term “beacon,” as it applies to the present disclosure, refers to atransmitter or transceiver which is placed on, within, or near an entitythat emits, at a minimum, a unique identifier (ID) that may be used touniquely identify the entity. For example, a beacon may be affixed to aplanter, and may transmit a unique ID which identifies the planter as“John Deere 1725 Planter: 10087.” In one embodiment, a beacon canoptionally collect information from an entity (e.g., telemetry from anentity connected wired or wirelessly to the beacon). For example, abeacon placed on, within, or near a fuel tank may be able to transmit aunique ID identifying the fuel tank as well as transmit fuel tankcharacteristic information including, but not limited to, the fuellevel, type of fuel within the tank, and the like. Beacons may also beable to transmit information regarding the beacon itself (e.g., beaconbattery health, beacon signal strength, and the like).

The term “scanner,” as it applies to the present disclosure, refers to atransceiver device which is placed on, within, or near an entity thatemits a unique identifier (ID) that may be used to uniquely identify theentity, scans for the unique ID's transmitted by beacons and otherscanners, and logs and/or transmits collected data with a time stamp andlocation to a remote database. Similar to beacons, scanners mayoptionally collect information from an entity with which they arerelated. For example, a scanner placed on or within a tractor may beable to collect information regarding the tractor including, but notlimited to, tractor fuel level, tractor speed, and the like. A scannermay optionally collect other information transmitted from beacons toidentify properties of the beacons (e.g., beacon battery health, and thelike) or entities with which the beacons are connected (e.g., fuel tanklevel, vehicle type, and the like).

The term “association,” as it applies to the present disclosure, refersto a group of two or more entities which occupy the same space. Twoentities that are within a certain distance of each other may be said tobe in a “spatial relationship” with one another. For example, a beaconmay be placed on a planter (Planter ID: 10087) and a scanner may beplaced on a tractor (Tractor ID: 62065). When the tractor comes within aspecified distance of the planter, the tractor and planter may be saidto be in a “spatial relationship” and form an association(“10087”+“62065”=Association 1). Continuing with the same example, thetractor is driven by a user, who has on their person a cell phone. Theuser's cell phone may also act as a scanner and/or beacon, and thereforebe identified by a unique ID. In this regard, the cell phone (e.g., theuser), the tractor, and the planter may all be in a spatialrelationship, and thus form a single association(“10087”+“62065”+“12345”=Association 1). It is contemplated that asingle association may be made up of any number of entities in a spatialrelationship with one another. For the purposes of this disclosure, theterms “association” and “spatial relationship” may be usedinterchangeably, unless noted otherwise herein.

The term “operation,” as it applies to the present disclosure, refers toan association as it moves through time and space. For example,continuing with the example above, a user, tractor, and planter may formAssociation 1 when they are in a spatial relationship with one another.As Association 1 continues over time, and as Association 1 movesthroughout a field, it could be determined that Association 1 isperforming a planting “operation.” This planting operation may simply bereferred to as Operation 1. Data associated with an operation mayinclude the data of the entities in the association (e.g., user phonedata, tractor data, planter data), the time the operation takes place(e.g., starting time, duration, ending time), and the location of theoperation (e.g., GPS coordinates over time, which field, and the like).

The terms “geo-fence,” “geo-fenced boundary,” “geo-fenced area,” andlike terms, as they apply to the present disclosure, refer to anygeographical area or region. By way of example, a geo-fenced area may bedefined by a series of GPS coordinates, or may be defined as a regionrelative to a particular entity. It is contemplated that a user maydefine one or more geo-fenced boundaries as areas in which the userdesires to track associations and operations. For example, a user maydefine the outer perimeter of a field as a first geo-fenced boundarydefining a first geo-fenced area. In this same manner, the user maydefine the perimeter of a second field as a second geo-fenced boundarydefining a second geo-fenced area. By way of another example, ageo-fenced area may be defined as the region within a specified distanceof an entity. In this regard, it is contemplated that a geo-fenced areamay be stationary or mobile. It is contemplated that defining particulargeo-fenced areas may allow a user to track associations and operationsto particular areas, thereby allowing the user to track operation times,equipment costs, inventory usage, and the like to particular areas.

The term “catalyst,” as it applies to the present disclosure, refers tosoftware and/or hardware processes or systems which serve to expeditethe process of identifying operations. Catalysts may include, but arenot limited to, machine learning algorithms, smartphone applications(e.g., a “chatbot app”), and the like. For example, when a tractorenters a spatial relationship with a planter and forms an association,it may be unclear at the start whether the tractor is simply passing bythe planter or whether the planter will be hooked up the tractor tobegin a planting operation. It may be the case that, in order topositively identify a planting operation with a certain amount ofaccuracy, the tractor and planter may need to form an association for aspecified amount of time (e.g., form an association for twenty or moreminutes). In order to positively identify the planting operation moreeffectively and/or efficiently, a catalyst (e.g., “chatbot app”) maysend a query notification to the smartphone of the user of the tractor.The chatbot app may ask the user whether the user is performing aplanting operation, whereby the user may confirm or deny that a plantingoperation is being performed. In this regard, it is contemplated that acatalyst may allow the present disclosure to more effectively andefficiently identify operations.

Relationships between many devices on the farm currently have minimalelectronic integration and/or interaction. Such devices will be referredto for the remainder of this document as “entities.” Examples ofagricultural “entities” include several categories of machines andsensors. For example, entities may include self-propelled machines, suchas, but not limited to, tractors, combines, forage harvesters,self-propelled sprayers, trucks, pickups, cars, or other personalvehicles. By way of another example, entities may include agriculturalimplements, such as, but not limited to, seeding and tillage equipment,planting equipment, hay harvesting equipment, and grain carts. By way ofanother example, entities may include stationary machines, such as, butnot limited to, pivot irrigation systems, grain handling systems,livestock buildings (e.g., confinement facilities, and the like) andagricultural buildings (e.g., shops, machine sheds, and the like). Byway of another example, entities may include energy generation machines,such as, but not limited to, diesel-powered generators, wind energygenerators, and the like. By way of another example, entities mayinclude, but are not limited to, miscellaneous devices/systems (e.g.,in-field sensors, personal mobile phones, etc.), agricultural inventory(e.g., seed containers, chemical/fertilizer containers, etc.), livestock(e.g., individual hogs, cattle, chickens, etc.) livestock equipment(e.g., livestock holding areas, loading chutes, scales, etc.), transportequipment (e.g., cargo containers, belt loaders, etc.), warehouseinventory (e.g., pallets, shipping containers, forklifts, shelves,etc.), raw materials (e.g., felled trees, mined minerals, etc.),construction equipment (e.g., trailers, pumps, excavators, etc.) and thelike.

While much of the present disclosure focuses on “entities” in theagricultural context, this is done merely for illustrative purposes, andis not to be understood as a limitation on the present disclosure. Inthis regard, it is noted herein that the systems and methods of thepresent disclosure may be useful and may be implemented in a widevariety of environments outside of the agricultural context.

It is currently difficult to track inventory, associated input costs,and machines from one area on a farm down to the area where that entityis used. Similarly, it is currently difficult to track inventory on afarm down to the area where the inventory is actually consumed. It isbelieved that smarter methods are possible which would connect theinteraction of “entities” utilizing proximity sensing to automateotherwise repetitive, tedious, and error-prone tasks.

It is recognized herein that proximity sensing may be used to establisha virtual association between two or more entities or devices. Thisassociation can then be associated with many different properties,including: a) time b) location c) people d) proximity of other entities,e) other linked “entities,” f) properties/measurements of entitiesequipped with sensors, and the like. These associations become extremelypowerful when they can be tracked in real time. Furthermore, theseassociations may provide valuable information when they are correlatedto other external data sources, such as precision agricultural data.

Associations between entities may be used to track many tasks andoperations. For example, these associations may be used to, but are notlimited to, track equipment usage, reconcile man hours, reconcileinventory usage, and the like. For instance, an association between farmequipment and a user's cell phone may be used to reconcile man hours. Byway of another example, an association between a tractor and a tank asthe tractor pulls the tank throughout a field may be identified as an“fertilizing operation” and used to reconcile machine time for both thetractor and the tank, and may be used to reconcile how long thefertilization operation was carried out in each field, part of a field,etc. In this regard, it is contemplated that the present disclosure mayallow for input cost allocation across smaller land areas, trackharvested crop mass/volume (e.g., cost/acre, cost/ha, cost/bu, cost/kg).

For instance, the system of the present disclosure may identify anassociation (e.g., spatial relationship) between a tractor and a planter(e.g., Association 1). As the tractor and the planter remain in anassociation for an extended period of time, and as Association 1 movesthroughout a field, the system of the present disclosure may determinethat Association 1 is carrying out a planting operation (e.g., Operation1). As a farm owner, one important metric for determining the efficiencyof the tractor and the planter are their respective costs as compared totheir hours of operation. In this instance, the tractor amortized over 5years has an average annual cost of $31,000 and the planter amortizedover 3 years has an average annual cost of $24,000. The cost of runningthe tractor and planter (e.g., the cost of Operation 1) per hour equals$31,000/total tractor hours+$24,000/total planter hours. Therefore, thecost of Operation 1 would be $55,000/hours of running Operation 1. Inthis regard, if the Operation 1 were each operated for 250 hours, thiswould mean that Operation 1 (e.g., planting) would cost $220/hour ofOperation 1 ($55,000/250 hrs=$220/hr).

The relationships between “entities,” “associations,” and “operations,”as well as the attendant advantages that come with relating each of theaforementioned to one another, may be further described in terms of“atoms”, “molecules,” and “polymers,” and with further reference to FIG.1.

FIG. 1 illustrates a graphical display of a geo-fenced area 156, inaccordance with one or more embodiments of the present disclosure.

By way of example, consider a tractor moving by itself through a field.As a sole entity, the tractor may be considered an “atom.” Data pointsassociated with the tractor (e.g., atom) may include any number ofmetrics relating to the state of the tractor (e.g., atom) at a singlepoint in time including, but not limited to, the tractor's speed, fuellevel, and position.

By way of another example, and with reference made to FIG. 1, consider atractor pulling a planter through a field, which may be delineated by apre-defined geo-fenced boundary 156. When the tractor (e.g., an “atom”)and the planter (e.g., an “atom”) come into close proximity with oneanother, they may form a spatial relationship (e.g., an association),thereby forming a “molecule.” In this regard, a “molecule” may bedefined as two entities (e.g., atoms) in a spatial relationship with oneanother. Data points 150 for the tractor/planter association (e.g.,molecule) may include any number of metrics relating to the state of thetractor/planter molecule at a single point in time including, but notlimited to, tractor speed, tractor fuel level, planter seed level, andthe like. As the tractor/planter molecule move throughout thepre-defined geo-fenced boundary 156, data points 150 a, 150 b, 150 n maybe collected at any interval (e.g., regular intervals, random intervals,and the like).

Continuing with the same example, consider the tractor/planter moleculemoving throughout the field (e.g., pre-defined geo-fenced boundary 156).The addition of time and location data may thereby turn data points 150for the tractor/planter molecule into a “polymer segments” (e.g.,polymer segments 152). In this regard, a polymer segments 152 a, 152 b,152 c, 152 n connect data points 150. For example, if data points 150were collected for the tractor/planter polymer every ten seconds, thedistance by which first data point 150 a and second data point 150 b areseparated would be dependent on the speed of the tractor/plantermolecule. By determining the locations of the first data point 150 a andthe second data point 150 b, several metrics for polymer segment 152 awould be able to be determined including, but not limited to, thetractor's speed throughout the ten-second span, the difference in thetractor's fuel level throughout the ten-second span, the difference inthe planter's seed level throughout the ten-second span, the fuelefficiency of the tractor throughout the ten-second span, and the like.

Furthermore, polymer segments 152 may be analyzed such that each polymersegment 152 has an associated cost. By way of example, as thetractor/planter molecule moves throughout the field, a first data point150 a and a second data point 150 b may be collected for thetractor/planter molecule. By determining the difference in tractor fuellevels and planter seed levels between the first data point 150 a andthe second data point 150 b, and by multiplying these differences in therespective costs of fuel and seed, the cost associated with polymersegment 152 may be determined. The associated cost for each polymersegment may be more accurately determined by factoring in additionalfactors including, but not limited to, equipment depreciation betweenfirst data point 150 a and second data point 150 b, associated employeewages for the respective time period, and the like.

Continuing with the same example, polymer segments 152 a, 152 b, 152 c,152 n may be grouped together to form a single “polymer” (e.g., polymer154). The tractor/planter polymer 154 may be regarded as a singleplanting operation for the area contained within the pre-definedgeo-fenced area 156.

It is noted herein that collecting data at multiple hierarchygranularity levels (e.g., by data points, polymer segments, andpolymers) may allow a farm owner to break down fuel, cost, and materialallocations. Furthermore, collecting data points more or less frequently(e.g., greater or fewer data points 150) may allow a farm owner tofurther modify the granularity level and further refine break-downs forfuel, cost, and materials. It is further noted that collecting data atmultiple hierarchy granularity levels may allow a farm owner to breakdown fuel, cost, and material allocations down by area, from the fieldlevel, sub-field level, and the like.

In one embodiment, the present disclosure utilizes a series of scannersand/or beacons (generally referred to as “communication devices”) onmultiple entities in order to automatically obtain and record spatialrelationship data via proximity sensing. It is noted that beacons andscanners may refer to any transmitting, receiving, and/or transceivingdevice(s) capable of transmitting and/or receiving electromagneticsignals. In this regard, beacons and sensors may transmit any wired orwireless signal known in the art including, but not limited to, radiosignals, WiFi signals, Bluetooth signals, 3G signals, 4G signals, 4G LTEsignals, 5G signals, and the like. Those skilled in the art willrecognize that a wide variety of transmitting and transceiving devicesmay be used without departing from the spirit and scope of the presentdisclosure.

In one embodiment, the present disclosure may include a firstcommunication device (e.g., a beacon or scanner) associated with a firstentity, and an additional communication device (e.g., a scanner)associated with an additional entity. In another embodiment, the firstcommunication device and the additional transmitting device arecommunicatively couplable (e.g., the beacon and the scanner arecommunicatively couplable). In another embodiment, the system of thepresent disclosure is configured to identify associations (e.g., spatialrelationships) between the first communication device and the additionalcommunication device. In this regard, the system of the presentdisclosure may be used to track associations (e.g., spatialrelationships) between various agricultural entities including, but notlimited to, people, vehicles, tractors, planters, trailers, tanks, andthe like.

It is noted that a substantial amount of information may be obtainedsimply by tracking entities' proximity to each other. For example, afarm owner may attach a first communication device (e.g., a scanner) toa tractor, and an additional communication device (e.g., a cell phone)may track the location of an employee. Simply by tracking the spatialrelationship between the tractor and the employee (via the twotransmitting devices), the farm owner may be able to determine theamount of time an employee spent working on/with the tractor. Forinstance, the tractor's communication device, or the employee's cellphone, may transmit and/or store in memory the time in which the twoentities (the tractor and the employee) were within twenty feet of oneanother. In this regard, the two communication devices may transmitand/or store in memory the time in which the two communication devicesformed an association. By tracking and storing the associationinformation, a farm owner may be able to determine when and how long theemployee was working on/with the tractor. This information maysubsequently be used to reconcile employee hours and/or pay.

By way of another example, communication devices may be placed on a fueltank, on a tractor, and on an employee (via the employee's cell phone),respectively. For instance, a beacon may be placed on the fuel tank, afirst scanner may be placed on the tractor, and the employee's cellphone may function as a second scanner. When employee comes within aspecified distance of the tractor, the scanner on the tractor and theemployee's cell phone may identify that the employee and the tractor arein a spatial relationship, and therefore form an association(Association 1). When the employee drives the tractor within a certainproximity to the beacon on the gas tank, the system of the presentdisclosure may detect a spatial relationship between the threecommunication devices (e.g., the scanner on the tractor, the employee'scell phone, and the beacon on the gas tank). In this regard, the systemof the present disclosure may identify that the three communicationdevices form a single association (Association 2). By identifying thisassociation, a farm owner may be able to determine that a particularemployee (associated with the employee's cell phone) fueled up thetractor (associated with the scanner on the tractor) with a particulargas tank (associated with the beacon on the tank) at a particular time.

In another embodiment, the present disclosure may simplify data trackingand analysis by grouping recurring associations (e.g., spatialrelationships) into “operations.” For instance, referring again to theexample above, the association between the employee, the tractor, andthe gas tank may exist for a period of ten minutes (e.g., theapproximate length of time necessary to fuel the tractor). After tenminutes, the three-way association (e.g., Association 2: the associationbetween the tractor, employee, and the gas tank) may disassociate,giving way to the single two-way association (Association 1) between thetractor and the employee (suggesting the employee has completed fuelingand is driving away). In this regard, by adding the time related to thethree-way association, the system of the present disclosure may groupthe association including the employee, the tractor, and the gas tankinto a single “fueling operation.” It is noted that grouping variousrecurring spatial relationships may allow a user to more accurately andefficiently track and analyze large volumes of data.

Continuing with the same example, it has been previously noted hereinthat scanners and beacons may be configured not only to transmit uniqueIDs to identify the entities with which they are related, but to alsoreceive and transmit data relating to the entities. In this regard, thescanner on the tractor may be configured to transmit tractor dataincluding, but not limited to, its fuel level. Similarly, the beacon onthe gas tank may be configured to transmit gas tank data inducing, butnot limited to, the type of gas in the tank and the fuel level of thetank. In this regard, as the fueling operation continues over time, thetractor scanner and fuel tank beacon may transmit their respective fuellevels. In this regard, the system of the present disclosure may be usedas a check for farm owners, allowing the farm owner to ensure that thefuel removed from the gas tank matches the fuel added to the tractor(e.g., ensure employees are not taking fuel for personal use).Furthermore, tracking the amount of fuel used by each entity throughouta given period of time may help a farm owner reconcile fuel usage acrossthe farm.

FIG. 2 illustrates a system 100 for determining spatial relationshipsbetween entities, in accordance with one or more embodiments of thepresent disclosure. In one embodiment, system 100 includes a firstcommunication device 101 a, an additional communication device 101 b, anetwork 112, a server 120, a controller 114, and a user interface 119.

It is contemplated herein that the first communication device 101 a andthe additional communication device 101 b may correspond to separateentities. For example, first communication device 101 a may correspondto a person (e.g., first communication device 101 a may be includeemployee's cell phone), and the additional communication device 101 bmay correspond to tractor.

In one embodiment, the first communication device 101 a and theadditional communication device 101 b may be configured to transmitentity ID signals 108. Entity ID signals 108 may be encoded with dataincluding, but not limited to, unique entity identifiers (e.g., entityIDs), communication device 101 data (e.g., first communication device101 a battery health, additional communication device 101 b batteryhealth, and the like), and the like.

In another embodiment, first communication device 101 a and theadditional communication device 101 b may include one or more sensorsconfigured to collect data. Data collected by the one or more sensors ofthe first communication device 101 a and/or the additional communicationdevice 101 b may include data regarding the surrounding environment(e.g., temperature, pressure, humidity, and the like), data associatedwith the entities with which the first communication device 101 a andthe additional communication device 101 b are associated, and the like.By way of example, if the first communication device 101 a wereassociated with a tractor, one or more sensors of first communicationdevice 101 a may collect data regarding the speed of the tractor, thefuel level of the tractor, the mileage of the tractor, and the like. Inthis regard, it is contemplated that entity ID signals 108 may includedata collected by the first communication device 101 a and theadditional communication device 101 b.

In another embodiment, first communication device 101 a and theadditional communication device 101 b may include a controller includingone or more processors and memory. The memory may be configured to storedata of system 100 including, but not limited to, collected data, datareceived via entity ID signals 108, and the like. In another embodiment,the first communication device 101 a and/or the additional communicationdevice 101 b may include GPS circuitry configured to receive GPSpositional information. In this regard, one or more processors of firstcommunication device 101 a and/or the additional communication device101 b may be configured to extract GPS positional information receivedfrom the GPS circuitry to determine the GPS position of firstcommunication device 101 a and/or the additional communication device101 b.

It is noted herein that system 100 is not limited to the configurationdepicted in FIG. 2 depicting a first communication device 101 a and theadditional communication device 101 b. In this regard, system 100 mayinclude any n number of communication devices 101 (e.g., nthcommunication device 101 n) without departing from the spirit and scopeof the present disclosure.

In one embodiment, the first communication device 101 a and theadditional communication device 101 b are directly or indirectly coupledto a server 120 and a controller 114 via a network 112. In this regard,first communication device 101 a and/or the additional communicationdevice 101 b may include network interface circuitry. It is noted hereinthat the network interface circuitry of first communication device 101 aand/or additional communication device 101 b may include any networkinterface for interacting with a network 112 known in the art. Inanother embodiment first communication device 101 a and/or theadditional communication device 101 b may be configured to transmitnetwork signals 110 to network 112. In one embodiment, network signals110 may include any data stored in the memory of first communicationdevice 101 a and/or the additional communication device 101 b. Forexample, network signals 110 may include, but are not limited toincluding, data associated with entity ID signals 108 received fromother communication devices, data collected by one or more sensors offirst communication device 101 a and/or the additional communicationdevice 101 b, and the like.

It is noted that a network interface (not shown) of first communicationdevice 101 a and/or the additional communication device 101 b mayinclude any network interface device suitable for interfacing withnetwork 112. For example, the network interface circuitry may includewireline-based interface devices (e.g., DSL-based interconnection,cable-based interconnection, T9-based interconnection, and the like). Inanother embodiment, the network interface circuitry may include awireless-based interface device employing GSM, GPRS, CDMA, EV-DO, EDGE,WiMAX, LTE, WiFi protocols, RF, LoRa, and the like.

As noted previously herein, communication devices 101 may be directly orindirectly communicatively coupled to network 112. In this regard,communication devices 101 may be communicatively coupled to one or moredevices, which may then be directly or indirectly communicativelycoupled to network 112. For example, as described in further detailherein with respect to FIG. 5E, communication devices 101 may becommunicatively coupled to a base station device 140, wherein the basestation device 140 is communicatively coupled to network 112. In thisexample, base station device 140 may be located in a centralizedlocation with respect to the communication devices 101, such as atop afence post, on top of a barn, and the like.

In another embodiment, network 112 may be configured to receive networksignals 110 transmitted by first communication device 101 a and/or theadditional communication device 101 b. It is noted herein that network112 may include any wireless and/or wireline network protocol known inthe art. For example, the network 112 may include, but is not limitedto, an internet or an intranet (e.g., LAN, WLAN and the like). By way ofanother example, network 112 may include a cloud-based architecture.

In another embodiment, system 100 includes a server 120 including one ormore processors 122 and memory 124. In another embodiment, server 120 iscommunicatively coupled to the communication devices via network 112 viaa network interface 130. The network interface 130 may include anynetwork interface device known in the art. For instance, the networkinterface 130 may include wireline-based interface devices (e.g.,DSL-based interconnection, Cable-based interconnection, T9-basedinterconnection, and the like). In another instance, the networkinterface devices may include a wireless-based interface deviceemploying GSM, GPRS, CDMA, EV-DO, EDGE, WiMAX, 4G, 4G LTE, 5G, Wi-fiprotocols, and the like. By way of another example, server 120 mayinclude a cloud based architecture.

In one embodiment, one or more processors 122 of server 120 areconfigured to execute a set of program instructions stored in memory124. In one embodiment, the one or more processors 122 are configured tocarry out one or more steps of the present disclosure.

In one embodiment, the one or more processors 122 are configured tocause the server 120 to receive data stored in network signals 110 vianetwork 112. In another embodiment, the one or more processors 122 areconfigured to identify associations (e.g., spatial relationships)between two or more entities. In another embodiment, the one or moreprocessors 122 are configured to store association data (e.g., spatialrelationship data) in memory 124. In another embodiment, the one or moreprocessors 122 are configured to identify operations based on thereceived association data. In another embodiment, the one or moreprocessors 122 are configured to store operation data in memory 124. Inanother embodiment, the one or more processors 122 are configured toinitiate a catalyst in order to more accurately and/or efficientlyidentify operations. In another embodiment, the one or more processors122 are configured to analyze received data relative to pre-definedgeo-fenced boundaries.

In one embodiment, the one or more processors 122 are configured tocause the server 120 to receive data stored in network signals 110 vianetwork 112. In one embodiment, the one or more processors 122 of server120 are configured to identify associations (e.g., spatialrelationships) between communication devices (e.g., association betweenthe first communication device 101 a and the additional communicationdevice 101 b, and the like). As noted previously herein, an associationrefers to a group of two or more entities which occupy the same space.Due to the fact that each entity may correspond to an individualcommunication device (e.g., a first entity with the first communicationdevice 101 a, a second entity with the second communication device 101b) the one or more processors 122 may be configured to identify anassociation between two or more entities when the two or more entitiesare within a specified distance of one another. In this regard, aspatial relationship between two or more entities (e.g., an association)may include, but is not limited to, relative distances between two ormore communication devices corresponding with two or more entities.

In one embodiment, the one or more processors 122 may identify anassociation (e.g., spatial relationship) between the first communicationdevice 101 a and the additional communication device 101 b based on GPSpositioning data received by the first communication device 101 a and/orthe additional communication device 101 b. After receiving the GPSpositions of the first communication device 101 a and the additionalcommunication device 101 b via network 112, the one or more processors122 may then be configured to determine the distance between the firstcommunication device 101 a and the additional communication device 101 bto determine whether the two communication devices are in close enoughproximity to be in an association (e.g., in a spatial relationship). Inthis same regard, the one or more processors 122 may be configured todetermine the distances between the first communication device 101 a andthe additional communication device 101 b in order to identifyassociations between each respective communication device.

By way of another example, if the entity ID signals 108 and/or networksignals 110 do not include GPS data indicating the GPS position of thefirst communication device 101 a and/or the additional communicationdevice 101 b, system 100 may still be configured to identify spatialrelationships between the respective communication devices based on theRelative Received Signal Strength (RSSI) values of the entity ID signals108 and/or network signals 110. Those skilled in the art will recognizethat RSSI values may be inversely related to the distance between thefirst communication device 101 a and the additional communication device101 b. In this regard, it is noted that entity ID signals 108transmitted by a first communication device 101 a which are in closeproximity to the additional communication device 101 b may exhibit highRSSI values. Conversely, it is noted that entity ID signals 108transmitted by a first communication device 101 a which is far away fromthe second communication device 101 b may exhibit low RSSI values. Inthis regard, one or more processors 122 may be configured to determinethe relative distance between first communication device 101 a and theadditional communication device 101 b based on the RSSI value of theentity ID signals 108 by associating high RSSI values with close spatialrelationships (e.g., short distances), and low RSSI values with largerspatial relationships (e.g., longer distances).

It is noted herein that the determination of spatial relationshipsbetween two or more communication devices is not limited to adetermination based on RSSI values. In this regard, it is contemplatedthat any proximity-based algorithm or method known in the art may beused without departing from the spirit and scope of the presentdisclosure.

It is noted herein that the one or more processors 122 of the server 120may be configured to identify associations between two or morecommunication devices based on pre-defined distances. For example, anassociation between a person (e.g., first communication device 101 a)and a trailer (e.g., additional communication device 101 b) may bedefined as existing when first communication device 101 a and theadditional communication device 101 b are within fifteen feet of eachother. By way of another example, the association between the person(e.g., first communication device 101 a) and the trailer (e.g.,additional communication device 101 b) may be defined as existing firstcommunication device 101 a and the additional communication device 101 bare within fifty feet of each other. It is noted herein that thedistances required for the identification of an association may bedependent on several factors, including, but not limited to, the type ofentities involved, the location of the entities, and the like. Forexample, a person (corresponding to a first communication device 101 a)may not operate a tractor (corresponding to a additional communicationdevice 101 b) without being in or directly on the tractor. As such, anassociation between the person (e.g., first communication device 101 a)and the tractor (e.g., additional communication device 101 b) may bedefined as existing when first communication device 101 a and theadditional communication device 101 b are within five feet of eachother. On the other hand, in order to load a tractor (corresponding to afirst communication device 101 a) with contents contained on a pallet(corresponding to an additional communication device 101 b), the tractormay be parked fifteen feet from the pallet. As such, an associationbetween the tractor and the pallet may be defined as existing when firstcommunication device 101 a and the additional communication device 101 bare within twenty feet of each other.

In another embodiment, the one or more processors 122 are configured tostore association data (e.g., spatial relationship data) in memory 124.Association data may include, but is not limited to, the GPS position ofeach entity in the association (e.g., GPS position of firstcommunication device 101 a, GPS position of additional communicationdevice 101 b, and the like), entity data (e.g., fuel level of entity,speed of entity, and the like), surrounding environment data (e.g.,temperature, pressure, moisture, and the like) and the like. In oneembodiment, all data transmitted and stored in memory 124 istime-stamped.

In another embodiment, the one or more processors 122 of server 120 maybe configured to filter and/or sort entity and association data inmemory 124 using any sorting or filtering operation known in the art.For example, the one or more processors 122 may be configured to sortassociation data in memory 124 based on each identified association. Forexample, the one or processors 122 may sort association data in memory124 in a database according to entity and/or association (e.g., Entity1, Entity 2, Entity n, Association 1, Association 2, Association n).

In another embodiment, the one or more processors 122 may be configuredto identify operations based on the received association data. As notedpreviously herein, an “operation” refers to an association as it movesthrough time and space. For example, a user (e.g., a first communicationdevice 101 a), tractor (e.g., an additional communication device 101 b),and planter (e.g., an nth communication device 101 n) may form anassociation (e.g., Association 1) when they are in a spatialrelationship with one another. As Association 1 continues over time, andas Association 1 moves throughout a field, it could be determined thatAssociation 1 is performing a planting “operation.” This plantingoperation may simply be referred to as Operation 1.

In this regard, the one or more processors 122 may be configured toidentify and store operation data in memory 124. As noted previouslyherein, the one or more processors 122 may be configured to storeoperation data in memory 124 using any sorting/filtering operation knownin the art. For example, the one or more processors 122 may sortoperation data in memory 124 in a database according to each identifiedoperation (e.g., Operation 1, Operation 2, Operation n).

In another embodiment, the one or more processors 122 may be configuredto initiate a catalyst in order to more accurately and/or efficientlyidentify operations. As noted previously herein, the term “catalyst,” asit applies to the present disclosure, refers to software and/or hardwareprocesses or systems which serve to expedite the process of identifyingoperations. Catalysts may include, but are not limited to, machinelearning algorithms, smartphone applications (e.g., a “chatbot app”),and the like. For example, the one or more processors 122 may identifyan association (Association 1) between a user (e.g., first communicationdevice 101 a), a tractor (e.g., an additional communication device 101b), and a planter (e.g., an nth communication device 101 n). Uponidentifying Association 1, the one or more processors 122 may beconfigured to cause the server to send a query to a chatbot app on theuser's cell phone (e.g., first communication device 101 a). The chatbotapp may display a query to the user asking the user whether the user isperforming a planting operation, whereby the user may confirm or denythat a planting operation is being performed. If the user responds“Yes,” the one or more processors 122 may be configured to identifyAssociation 1, as it moves throughout space and time, as a “PlantingOperation” (e.g., Operation 1). In this regard, the one or moreprocessors may be configured to collect and store Operation 1 data inmemory 124.

In another embodiment, the one or more processors 122 may be configuredto analyze received data relative to pre-defined geo-fenced boundaries.As noted previously herein, the terms “geo-fence,” “geo-fencedboundary,” and “geo-fenced area,” as they apply to the presentdisclosure, refer to a geographical area defined by a series of GPScoordinates. It is contemplated that a user may define one or moregeo-fenced boundaries as areas in which the user desires to trackassociations and operations. For example, a user may define the outerperimeter of a field as a first geo-fenced boundary defining a firstgeo-fenced area, and the one or more processors 122 may store the firstgeo-fenced boundary in memory 124. In this same manner, the user maydefine the perimeter of a second field as a second geo-fenced boundarydefining a second geo-fenced area, and the one or more processors 122may store the second geo-fenced boundary in memory 124. In this regard,it is contemplated that the one or more processors 122 may be configuredto analyze received entity, association, and operation data relative tothe pre-defined geo-fenced boundaries.

For example, the one or more processors 122 may be configured todetermine whether a particular association is located within or outsideparticular geo-fenced boundaries. By way of another example, asOperation 1 (e.g., a planting operation) moves throughout a first field(defined by a first geo-fenced boundary), the one or more processors 122may be configured to analyze whether Operation 1 remains in the firstfield, or crosses the geo-fenced boundary into a second field defined bya second geo-fenced boundary.

It is contemplated that the one or more processors 122 may storegeo-fencing data in memory 124 along with the stored entity,association, and operation data. For example, a database of operationdata may include, but is not limited to including, the entity data ofthe entities in the operation, time-stamped data, position of theoperation relative to geo-fenced boundaries, and the like. In thisregard, it is contemplated that system 100 may be used to track themovements of entities, associations, and operations over time relativeto geo-fenced boundaries.

In another embodiment, system 100 includes a controller 114communicatively coupled to the server 120 via network 112 and networkinterface 128. The network interface 128 may include any networkinterface device known in the art. For instance, the network interfacedevice 128 may include wireline-based interface devices (e.g., DSL-basedinterconnection, Cable-based interconnection, T9-based interconnection,and the like). In another instance, the network interface devices mayinclude a wireless-based interface device employing GSM, GPRS, CDMA,EV-DO, EDGE, WiMAX, 4G, 4G LTE, 5G, Wi-fi protocols, and the like.

In one embodiment, controller 114 includes one or more processors 116and memory 118. In another embodiment, the one or more processors 116may be configured to execute a set of program instructions stored inmemory 118, wherein the set of program instructions are configured tocause the one or more processors 116 to carry out the steps of thepresent disclosure. It is noted herein that the discussion hereinregarding server 120, one or more processors 122, and memory 124 mayalso be regarded as applying to controller 114, one or more processors116, and memory 118, unless noted otherwise herein.

It is noted herein that the one or more components of system 100 may becommunicatively coupled to the various other components of system 100 inany manner known in the art. For example, the one or more processors122, 116 may be communicatively coupled to each other and othercomponents via a wireline (e.g., copper wire, fiber optic cable, and thelike) or wireless connection (e.g., RF coupling, IR coupling, datanetwork communication (e.g., WiFi, WiMax, Bluetooth and the like).

In one embodiment, a user interface 119 is communicatively coupled tothe controller 114. In one embodiment, the user interface 119 includes adisplay used to display data of the system 100 to a user. The display ofthe user interface 119 may include any display known in the art. Forexample, the display may include, but is not limited to, a liquidcrystal display (LCD), an organic light-emitting diode (OLED) baseddisplay, or a CRT display. Those skilled in the art should recognizethat any display device capable of integration with a user interface 119is suitable for implementation in the present disclosure. In anotherembodiment, a user may input selections and/or instructions responsiveto data displayed to the user via the user interface 119.

In another embodiment, the user interface 119 may include, but is notlimited to, one or more desktops, laptops, tablets, smartphones, smartwatches, or the like. In one embodiments, a user may use the userinterface 119 in order to view entity, association, operation, GPS, andgeo-fenced data stored in memory 124 of server 120 or stored in memory118 of controller 114. For example, a farm owner may desire to go backand reconcile fuel usage across the farm at the end of a month. The farmowner may have a first gas pump corresponding to a first communicationdevice 101 a and a second gas pump corresponding to an additionalcommunication device 101 b. Using a computer or smart phone (e.g., userinterface 119), the farm owner could review all the association data(e.g., spatial relationship data) in which first communication device101 a and the additional communication device 101 b were associated. Forinstance, pulling up all association data for the first communicationdevice 101 a, the farm owner may determine that the first gas pump(e.g., first communication device 101 a) was in an association withfifteen vehicles throughout the month. Through the user interface 119,the owner could review, among other things, which vehicles were fueledwith which fuel tanks at particular times throughout the month.

It is noted herein that a wireless electronics device (e.g., a cellphone, tablet, smart watch, and the like) may serve both as acommunication device 101 and as a controller 114/user interface 119. Forexample, a user may have their smartphone on them as they work in afield. The smartphone may act as communication device 101 whichidentifies an entity (e.g., the user). Additionally, the user'ssmartphone may act as a user interface 119 with which the user mayaccess data stored on memory 124 of server 120 via network 112.

In another embodiment, user interface 119 may be used to deliver alertsto a user. Alerts delivered to the user interface 119 may include, butare not limited to, text messages, automated phone calls, emails,banners, messages via applications (“Apps”), chatbot apps, or the like.It is contemplated that the one or more processors 122, 116 may beconfigured to deliver an alert to the user interface 119 in varyingsituations. For example, the one or more processors 122, 116 may beconfigured to execute a set of program instructions stored in memory124, 118 which cause the user interface 119 to display an alert of acertain spatial relationship. For instance, a tractor equipped with afirst communication device 101 a may come in close proximity to gas tankwith an incorrect type of fuel equipped with an additional communicationdevice 101 b. In this example, an association between the tractor (e.g.,first communication device 101 a) and gas tank (e.g., additionalcommunication device 101 b) may be determined, suggesting that fuelingis or is about to take place. After detecting an improper association(e.g., spatial relationship between an incorrect gas tank for theparticular tractor), the one or more processors 122, 116 may cause theuser interface 119 to display an alert informing a user that someone maybe attempting to fuel the tractor with the incorrect fuel. It is notedthat such alerts may prevent wasting resources and prevent propertydamages.

By way of another example, one or more geo-fenced boundaries may bestored in memory 124, 118. Geo-fenced boundaries may be associated withan entire farm, particular fields, and the like. In this example, a userinterface 119 may display an alert informing a user that a vehicleequipped with a first communication device 101 a has left a geo-fencedboundary. By way of another example, a user interface 119 may display analert that a particular bag of fertilizer equipped with an additionalcommunication device 101 b has entered a geo-fenced boundary associatedwith the improper field for that bag of fertilizer. In this example, thealert on the user interface 119 may inform a user that the user, or athird person, may be attempting to use the fertilizer on an incorrectfield.

FIG. 3 illustrates a simplified block diagram of a beacon 102 fordetermining spatial relationships between entities, in accordance withone or more embodiments of the present disclosure. In one embodiment,beacon 102 includes one or more sensors 103, one or more processors 105,memory 107, and communication circuitry 109.

It is contemplated herein that one or more communication devices 101 ofsystem 100 may include one or more beacons 102, as depicted in FIG. 3.By way of example, the additional communication device 101 b may includebeacon 102. However, it may be appreciated that communication devices101 are not limited to the configuration of the beacon 102 depicted inFIG. 3.

In one embodiment, beacon 102 may be configured to be placed on orwithin an entity such that the beacon 102 may be regarded ascorresponding with the entity and identifying the entity itself. Forexample, a beacon 102 placed on a tractor may be regarded as identifyingthe tractor. In this regard, it is noted that beacon 102 may includemechanical components and/or electrical circuitry configured tomechanically and/or communicatively couple the beacon 102 to aparticular entity (e.g., tractor, fuel tank, bailer, trailer, and thelike). In this regard, it is noted that beacon 102 may be affixed toentities using any method known in the art including, but not limitedto, adhesives, welding, straps, bolts, containment structures, and thelike. Alternatively, it is contemplated that beacon 102 may be placedwithin an entity.

In another embodiment, beacon 102 may include one or more sensors 103.In one embodiment, the one or more sensors 103 may be configured toreceive information associated with the surrounding environment and/orinformation associated with the entity corresponding to the beacon 102(e.g., telemetry from an entity connected wired or wirelessly to thebeacon 102). For example, if beacon 102 were placed on/within a fueltank, the one or more sensors 103 may be configured to collect dataincluding, but not limited to, the level of the fuel tank, the type offuel within the tank, the temperature of the tank, the temperature ofthe surrounding environment, and the like. It is noted herein that theone or more sensors 103 may include any sensors known in the art. Forexample, the one or more sensors 103 may include, but are not limitedto, one or more motion sensors (e.g., accelerometers), one or moretemperature sensors (e.g., RTDs, thermocouples, etc.), one or more lightsensors (e.g., diode, CCD, and etc.), one or more moisture sensors, andthe like. Furthermore, the one or more sensors 103 of beacon 102 mayinclude any sensors known in the art used to measure any characteristicor quality of the entity with which the beacon 102 corresponds. Forexample, if beacon 102 were attached to a tractor, the one or moresensors 103 may be configured to collect data regarding, among othercharacteristics, tractor make/model, fuel levels, mileage, and the like.

While FIG. 3 depicts beacon 102 as including one or more sensors 103,this is not to be regarded as a limitation of the present disclosure. Inthis regard, it is noted that beacon 102 need not include one or moresensors 103, and that beacon 102 may optionally not include one or moresensors 103 without departing from the spirit and scope of the presentdisclosure.

In another embodiment, beacon 102 may include one or more processors105. In another embodiment, the one or more processors 105 may beconfigured to execute a set of program instructions stored on memory107, wherein the set of program instructions are configured to cause theone or more processors 105 to carry out the various steps of the presentdisclosure.

In one embodiment, the one or more processors 105 may be configured toreceive data from the one or more sensors 103. In another embodiment,the one or more processors 105 may be configured to time-stamp the datareceived from the one or more sensors 103 and store the time-stampeddata in memory 107.

In another embodiment, beacon 102 may include communication circuitry109. Communication circuitry 109 may include any communication circuitryknown in the art. By way of example, communication circuitry 109 mayinclude a receiver, a transmitter, and/or a transceiver. In oneembodiment, communication circuitry 109 may be configured to transmitentity ID signals 108, wherein entity ID signals 108 include a uniqueidentifier which may be used to uniquely identify the entity with whichthe beacon 102 corresponds. For example, if beacon 102 were placedon/within a fuel tank, communication circuitry 109 may be configured totransmit entity ID signals 108, wherein entity ID signals 108 include aunique identifier (ID) which may be used to uniquely identify the fueltank (e.g., Fuel Tank ID: 10954). In another embodiment, communicationcircuitry 109 may be configured to transmit entity ID signals 108,wherein entity ID signals 108 include data associated with the beacon102 and/or the entity with which the beacon 102 corresponds. Forexample, communication circuitry 109 may be configured to transmitsignals 108, wherein entity ID signals 108 include data including, butnot limited to, beacon battery health, beacon signal strength, and thelike. By way of another example, if beacon 102 were placed on/within afuel tank, entity ID signals 108 may include data relating to the fueltank including, but not limited to, the type of fuel in the tank, thelevel of the fuel tank, humidity level, surrounding temperature, and thelike.

It is noted herein that entity ID signals 108 may include any type ofsignals known in the art. For example, communication circuitry 109 maybe configured to transmit any type of entity ID signal 108 including,but not limited to, RF signals, Bluetooth signals, WiFi signals, 3Gsignals, 4G signals, 4G LTE signals, 5G signals, wireline signals, andthe like. In another embodiment, communication circuitry 109 may beconfigured to receive entity ID signals 108 from other communicationdevices.

In another embodiment, communication circuitry 109 may transmit entityID signals 108 at any interval known in the art including, but notlimited to, continuously, substantially continuously, regular intervals,irregular intervals, and the like. For example, communication circuitry109 may be configured to transmit entity ID signals 108 continuously. Byway of another example, communication circuitry 109 may be configured totransmit entity ID signals 108 every two minutes. In another embodiment,when beacon 102 is out of range, blocked by physical structures, impededby weather phenomena, or otherwise unable to transmit entity ID signals108, the one or more processors 105 may be configured to store data inmemory 107 until such time that communication circuitry 109 is able totransmit entity ID signals 108. For example, if beacon 102 were out ofrange and unable to transmit entity ID signals 108, one or moreprocessors 105 may be configured to store data in memory 107 while thebeacon 102 is out of range. When the beacon 102 returns within rangeand/or the communication circuitry 109 otherwise regains the ability totransmit entity ID signals 108, the one or more processors 105 may causethe communication circuitry 109 to receive the data stored in memory 107and transmit the data via entity ID signals 108.

FIG. 4 illustrates a simplified block diagram of a scanner 104 fordetermining spatial relationships between entities, in accordance withone or more embodiments of the present disclosure. In one embodiment,scanner 104 includes one or more sensors 103, one or more processors105, a memory 107, communication circuitry 111, GPS circuitry 117, andnetwork circuitry 115.

It is contemplated herein that one or more communication devices 101 ofsystem 100 may include one or more scanners 104, as depicted in FIG. 4.By way of example, the first communication device 101 a may includescanner 104. By further way of example, the first communication device101 a may include a scanner 104, and the additional communication device101 b may include a beacon 102. However, it may be appreciated thatcommunication devices 101 are not limited to the configuration of thebeacon 102 and or the scanner 104 depicted in FIGS. 3 and 4.

It is noted herein that the discussion associated with beacon 102 inFIG. 3 may be regarded as applying to scanner 104 in FIG. 4, unlessnoted otherwise herein.

In one embodiment, communication circuitry 111 may be configured toreceive entity ID signals 108 including, but not limited to, one or moresignals transmitted from one or more other communication devices 101(e.g., beacons 102 other scanners 104, and the like). In anotherembodiment, GPS circuitry 117 may be configured to receive GNSS signals113 including global position information from a global position system(e.g., GPS, GNSS, GLONASS and the like). In this regard, GPS circuitry117 may be configured to receive GPS positional data regarding theposition of scanner 104. It is noted herein that, communicationcircuitry 111, GPS circuitry 117, and network circuitry 115 may includeany communication circuitry known in the art, including receivers,transmitters, transceivers, and the like. Furthermore, communicationcircuitry 111, GPS circuitry 117, and network circuitry 115 may becontained separately as distinct components or, additionally and/oralternatively, may be combined in one or more common housings (e.g., oneor more common receivers, one or more common transmitters, one or morecommon transceivers, and the like) without departing from the spirit andscope of the present disclosure.

In one embodiment, communication circuitry 111 may be configured toreceive entity ID signals 108 from one or more communication devices(e.g., beacon 102 or other scanner 104), extract the data associatedwith entity ID signals 108, and transmit the extracted data to one ormore processors 105. In another embodiment, communication circuitry 111is configured to transmit entity ID signals 108. In one embodiment,entity ID signals 108 may include data including, but not limited to, aunique entity identifier (e.g., entity ID), data associated with thescanner 104 (e.g., scanner 104 battery health, and the like), dataassociated with the entity with which the scanner 104 corresponds (e.g.,fuel level, vehicle speed, and the like), environmental data (e.g.,atmospheric pressure, temperature, and the like) and the like.

In another embodiment, GPS circuitry 117 may be configured to receiveGNSS signals 113, extract the data associated with GNSS signals 113, andtransmit the extracted data to one or more processors 105.

In another embodiment, scanner 104 may include one or more sensors 103.One or more sensors 103 may be configured to receive informationassociated with the surrounding environment and/or informationassociated with the entity corresponding to the scanner 104 (e.g.,telemetry from an entity connected wired or wirelessly to the scanner104). For example, if scanner 104 were placed on/within a tractor, theone or more sensors 103 may be configured to collect data including, butnot limited to, the level of the tractor's fuel tank, the mileage of thetractor, the speed of the tractor, the temperature of the surroundingenvironment, and the like. It is noted herein that the one or moresensors 103 may include any sensors known in the art. For example, theone or more sensors 103 may include, but are not limited to, one or moremotion sensors (e.g., accelerometers), one or more temperature sensors(e.g., RTDs, thermocouples, etc.), one or more light sensors (e.g.,diode, CCD, and etc.) and/or one or more moisture sensors. Furthermore,the one or more sensors of scanner 104 may include any sensors known inthe art used to measure any characteristic or quality of the entity withwhich it is associated.

While FIG. 4 depicts scanner 104 as including one or more sensors 103,this is not to be regarded as a limitation of the present disclosure. Inthis regard, it is noted that scanner 104 need not include one or moresensors 103, and that scanner 104 may optionally not include one or moresensors 103 without departing from the spirit and scope of the presentdisclosure.

In another embodiment, scanner 104 may include one or more processors105. In another embodiment, the one or more processors 105 may beconfigured to execute a set of program instructions stored in memory107, the set of program instructions configured to cause the one or moreprocessors 105 to carry out the various steps of the present disclosure.In one embodiment, the one or more processors 105 may be configured toreceive data associated with entity ID signals 108 and GNSS signals 113.In another embodiment, the one or more processors 105 may be configuredto receive data from the one or more sensors 103. In another embodiment,the one or more processors 105 may be configured to time-stamp the datareceived from the communication circuitry 111, GPS circuitry 117, and/orone or more sensors 103 and store the time-stamped data in memory 107.

In another embodiment, scanner 104 may include network circuitry 115. Inone embodiment, network circuitry 115 may be configured to receivenetwork signals 110 from an outside network 112. In another embodiment,the one or more processors 105 of scanner 104 may be configured todirect the network circuitry 115 to transmit network signals 110 to anoutside network 112. In this regard, network circuitry 115 may includeany network interface circuitry known in the art. In one embodiment,network signals 110 may include any data stored in memory 107. Forexample, network signals 110 may include, but are not limited toincluding, data associated with entity ID signals 108 received fromother communication devices (e.g., beacons 102, other scanners 104),data associated with received GNSS signals 113 (e.g., positional data),data collected by the one or more sensors 103, and the like.

It is noted that the network circuitry 115 of scanner 104 may includeany network interface circuitry or network interface device suitable forinterfacing with network 112. For example, the network interfacecircuitry may include wireline-based interface devices (e.g., DSL-basedinterconnection, cable-based interconnection, T9-based interconnection,and the like). In another embodiment, the network interface circuitrymay include a wireless-based interface device employing GSM, GPRS, CDMA,EV-DO, EDGE, WiMAX, 4G, 4G LTE, 5G, WiFi protocols, RF, LoRa, and thelike.

It is noted herein that entity ID signals 108 and network signals 110may include any type of signals known in the art. For example, networkcircuitry 115 may be configured to transmit any type signal including,but not limited to, RF signals, Bluetooth signals, WiFi signals, 3Gsignals, 4G signals, 4G LTE signals, 5G signals, wireline signals, andthe like.

In another embodiment, network circuitry 115 may transmit entity IDsignals 108 and/or network signals 110 at any interval known in the artincluding, but not limited to, continuously, substantially continuously,regular intervals, irregular intervals, and the like. For example,network circuitry 115 may be configured to transmit entity ID signals108 and network signals 110 continuously. By way of another example,network circuitry 115 may be configured to transmit entity ID signals108 and network signals 110 every two minutes. In another embodiment,when scanner 104 is out of range, blocked by physical structures,weather phenomena, or otherwise unable to transmit signals 108, 110 theone or more processors 105 may be configured to store data in memory 107until such time that network circuitry 115 is able to transmit signals108, 110. For example, if scanner 104 were out of range and unable tosignals 108, 110 one or more processors 105 may be configured to storedata in memory 107 while the scanner 104 is out of range. When thescanner 104 returns within range and/or the transmitter 115 otherwiseregains the ability to transmit signals 108, 110 the one or moreprocessors 105 may cause the network circuitry 115 to receive the datastored in memory 107 and transmit the data via signals 108, 110.

FIGS. 5A-5E illustrate a system 100 for determining spatialrelationships between entities, in accordance with one or moreembodiments of the present disclosure. It is noted herein that thediscussion associated with system 100 in FIG. 2 may be regarded asapplying to system 100 depicted in FIGS. 5A-5E, unless noted otherwiseherein. Similarly, it is noted herein that the discussion associatedwith system 100 in FIGS. 5A-5E may be regarded as applying to system 100depicted in FIG. 2, unless noted otherwise herein.

In one embodiment, as shown in FIG. 5A, system 100 includes a scanner104, a first beacon 102 a, a second beacon 102 b, a network 112, aserver 120, a controller 114, and a user interface 119. It iscontemplated that each of the communication devices (e.g., scanner 104,first beacon 102 a, and second beacon 102 b) may correspond to separateentities. For example, scanner 104 may correspond to a person (e.g.,scanner 104 is the employee's cell phone), the first beacon 102 a maycorrespond to a trailer (e.g., affixed to the trailer), and the secondbeacon 102 b may correspond to a pallet with materials (e.g., affixed tothe pallet).

In one embodiment, the first beacon 102 a and the second beacon 102 bmay be configured to transmit entity ID signals 108. Entity ID signals108 may be encoded with data including, but are not limited to, uniqueentity identifiers (e.g., entity IDs), beacon data (e.g., beacon 102 abattery health, beacon 102 b battery health), data collected by thesensors 103 of the first beacon 102 a, data collected by the sensors 103of the second beacon 102 b, and the like.

In another embodiment, the receiver 111 of scanner 104 may be configuredto receive entity ID signals 108. In another embodiment, the GPScircuitry 117 of scanner 104 may be configured to receive GNSS signals113 from satellite 121. In another embodiment, one or more sensors 103of scanner 104 may be configured to collect data including, but notlimited to, the data of the entity corresponding to the scanner 104, thesurrounding environment, and the like. In another embodiment, the one ormore processors 105 of scanner 104 may be configured to store data inmemory 107. For example, the one or more processors 105 of scanner 104may be configured to store in memory 107 data received from entity IDsignals 108, positioning data received from GNSS signals 113, datareceived from one or more sensors 103 of scanner 104, and the like.

In another embodiment, the scanner 104 is directly or indirectly coupledto a server 120 and a controller 114 via a network 112. In this regard,scanner 104 may include network interface circuitry (not shown). It isnoted herein that the network interface circuitry (not shown) of scanner104 may include any network interface for interacting with a network 112known in the art. In another embodiment, network circuitry 115 may beconfigured to transmit network signals 110 to network 112. In oneembodiment, network signals 110 may include any data stored in memory107. For example, signals 110 may include, but are not limited toincluding, data associated with entity ID signals 108 received fromother communication devices (e.g., beacons 102, other scanners 104),data associated with received GNSS signals 113 (e.g., positional data),data collected by the one or more sensors 103, and the like.

It is noted that the network interface (not shown) of scanner 104 mayinclude any network interface device suitable for interfacing withnetwork 112. For example, the network interface circuitry may includewireline-based interface devices (e.g., DSL-based interconnection,cable-based interconnection, T9-based interconnection, and the like). Inanother embodiment, the network interface circuitry may include awireless-based interface device employing GSM, GPRS, CDMA, EV-DO, EDGE,WiMAX, 4G, 4G LTE, 5G, WiFi protocols, RF, LoRa, and the like.

In one embodiment, the one or more processors 122 identify anassociation (e.g., spatial relationship) between the first beacon 102 aand the scanner 104 based on the positioning data received by thescanner 104 via GNSS signals 113 and the entity ID signals 108transmitted by the first beacon 102 a. For example, after receiving GNSSsignals 113, the one or more processors 105 of the scanner 104 mayextract the positioning data in order to determine the precise GPSposition of the scanner 104. Furthermore, the scanner 104 may receiveentity ID signals 108 from the first beacon 102 a. If the entity IDsignals 108 transmitted by the first beacon 102 a include the GPSposition of the first beacon 102 a, the one or more processors 105 ofscanner 104 would then be able to determine the GPS position of both thefirst beacon 102 a and the scanner 104, and transmit both GPS locationsto the one or more processors 122 of server 120 via network signals 110and network 112. After receiving the GPS positions of the first beacon102 a and the scanner 104 via network 112, the one or more processors122 may then be configured to determine the distance between the twocommunication devices (e.g., the first beacon 102 a and the scanner 104)to determine whether the two communication devices are in close enoughproximity to be in an association (e.g., in a spatial relationship). Inthis same regard, the one or more processors 122 may be configured todetermine the distances between each respective communication device(e.g., first beacon 102 a, second beacon 102 b, scanner 104) in order toidentify associations between each respective communication device.

By way of another example, if the entity ID signals 108 transmitted bythe first beacon 102 a do not include GPS data indicating the GPSposition of the first beacon 102 a, system 100 may still be configuredto identify spatial relationships between the respective communicationdevices based on the GPS position of the scanner 104 and the RelativeReceived Signal Strength (RSSI) values of the entity ID signals 108.Those skilled in the art will recognize that RSSI values may beinversely related to the distance between the communication device(e.g., the first beacon 102 a in this example) and the receiving device(e.g., the scanner 104 in this example). In this regard, it is notedthat entity ID signals 108 transmitted by first beacon 102 a which arein close proximity to the scanner 104 may exhibit high RSSI values.Conversely, it is noted that entity ID signals 108 transmitted by afirst beacon 102 a which is far away from the scanner 104 may exhibitlow RSSI values. In this regard, one or more processors 105 of scanner104 may be configured to determine the relative distance between thescanner 104 and the first beacon 102 a based on the RSSI value of theentity ID signals 108 transmitted by the first beacon 102 a byassociating high RSSI values with close spatial relationships (e.g.,short distances), and low RSSI values with larger spatial relationships(e.g., longer distances).

For example, after receiving GNSS signals 113, the one or moreprocessors 105 of the scanner 104 may extract the positioning data inorder to determine the precise GPS position of the scanner 104. Thescanner 104 may also receive entity ID signals 108 (without GPS positiondata) from the first beacon 102 a. Based on the RSSI value of thereceived entity ID signals 108, the one or more processors 105 of thescanner 104 may be configured to determine the distance between thescanner 104 and the first beacon 102 a. The one or more processors 105of the scanner 104 may then be configured to cause the scanner 104 totransmit the GPS position of the scanner 104 and the spatialrelationship data (e.g., distance) between the first beacon 102 a andthe scanner 104 to the server 120 via network signals 110 and network112. The one or more processors 122 of server 120 may then be configuredto identify the existence of an association between the scanner 104 andthe first beacon 102 a based on the GPS location of the scanner 104 andthe distance between the scanner 104 and the first beacon 102 a.

It is noted herein that the determination of spatial relationshipsbetween two or more communication devices is not limited to adetermination based on RSSI values. In this regard, it is contemplatedthat any proximity-based algorithm or method known in the art may beused without departing from the spirit and scope of the presentdisclosure.

It is noted herein that any of the steps performed by the one or moreprocessors 105 of the communication devices (e.g., beacons 102 a, 102 b,and scanner 104) may be performed by the one or more processors 122 ofthe server 120, and vice versa. For example, referring again to theexample above, instead of the one or more processors 105 of the scanner104 determining the distance between the scanner 104 and the firstbeacon 102 a based on the GPS position of the scanner 104 and the RSSIvalue of the received entity ID signals 108, the scanner 104 may insteadtransmit the GPS position of the scanner 104 and the RSSI value of thereceived entity ID signals 108 to the server 120 via network signals 110and network 112. In this regard, the one or more processors 122 of theserver 120 may be configured to receive GPS data of the scanner 104 andRSSI values of the received entity ID signals 108, determine thedistance between the scanner 104 and the first beacon 102 a, andidentify the existence of an association between the scanner 104 and thefirst beacon 102 a based on the calculated distance between the two.

FIG. 5B illustrates a system 100 for determining spatial relationshipsbetween entities, in accordance with one or more embodiments of thepresent disclosure. In one embodiment, system 100 includes a firstscanner 104 a, a second scanner 104 b, a first beacon 102 a, a network112, a server 120, a controller 114, and a user interface 119. It isnoted herein that the description associated with FIGS. 1 and 5A mayalso be regarded as applying to FIG. 5B, unless noted otherwise herein.

In one embodiment, system 100 displayed in FIG. 5B includes twoscanners: a first scanner 104 a and a second scanner 104 b. In oneembodiment, the second scanner 104 b may transmit entity ID signals 108to the first scanner 104 a. It is noted herein that multiple scanners(e.g., first scanner 104 a, second scanner 104 b) may transmit entity IDsignals 108 to each other. It is further noted herein that, due to thefact scanners 104 a, 104 b may receive GNSS signals 113 to determinetheir respective GPS positions, system 100 may be capable of moreaccurately determining the position of communication devices (e.g.,first scanner 104 a, second scanner 104 b, first beacon 102 a, secondbeacon 102 b, and the like) and the existence of associations andoperations when multiple scanners 104 a, 104 b are present.

FIG. 5C illustrates a system 100 for determining spatial relationshipsbetween entities, in accordance with one or more embodiments of thepresent disclosure. In one embodiment, system 100 includes a firstcommunication device 101 a, an additional communication device 101 b, anetwork interface 132, a network 112, a server 120, a controller 114,and a user interface 119. It is noted herein that the descriptionassociated with FIGS. 2 and 5A-5B may also be regarded as applying toFIG. 5C, unless noted otherwise herein.

In one embodiment, the first communication device 101 a may include aprocessor 134 and communication circuitry 136. Communication circuitry136 may include any communication circuitry known in the art including,but not limited to, a transmitter, a receiver, and/or a transceiver. Inone embodiment, first communication device 101 a and additionalcommunication device 101 b, as depicted in FIG. 5C, may include RFIDsensors. By way of example, first communication device 101 a may includean active transmitter, and the additional communication device 101 b mayinclude a passive transmitter. In this example, when the passivetransmitter (e.g., additional communication device 101 b) comes intoclose proximity with the active transmitter (e.g., first communicationdevice 101 a), communication circuitry 138 may transmit entity IDsignals 108 b to first communication device 101 a. It is noted hereinthat the examples given are not to be regarded as limiting. In thisregard, first communication device 101 a and additional communicationdevice 101 b may include any transmitter (e.g., active transmitter,passive transmitter), receiver, transceiver, RFID tag, or RFID readerknown in the art.

FIG. 5D illustrates a system 100 for determining spatial relationshipsbetween entities, in accordance with one or more embodiments of thepresent disclosure. In one embodiment, system 100 includes a firstcommunication device 101 a, an additional communication device 101 b, anetwork 112, a server 120, a controller 114, and a user interface 119.It is noted herein that the description associated with FIGS. 2 and5A-5C may also be regarded as applying to FIG. 5D, unless notedotherwise herein.

In one embodiment, system 100 may be configured to receive a pre-definedgeo-fenced area 129. By way of example, a user may input pre-definedgeo-fenced area 129 via user interface 119. Pre-defined geo-fenced areamay include any mobile or immobile area including, but not limited to,the perimeter of a farm, the perimeter of a field, a radius around agarage, a radius around an entity (e.g., a radius around a tractor), andthe like. As displayed in FIG. 5D, a first communication device 101 aand an additional communication device 101 b may be located within thepre-defined geo-fenced area 129.

In one embodiment, system 100 may be configured to transmit networksignals 110 to network 112, identify a spatial relationship, and thelike, based on the location of the communication devices (e.g., firstcommunication device 101 a, additional communication device 101 b, andthe like) relative to pre-defined geo-fenced area 129. By way ofexample, system 100 may identify a spatial relationship between thefirst communication device 101 a and the additional communication device101 b only when the first communication device 101 a and the additionalcommunication device 101 b are within the pre-defined geo-fenced area129. It is noted herein that this example is not to be regarded aslimiting, and is provided purely by way of example.

FIG. 5E illustrates a system 100 for determining spatial relationshipsbetween entities, in accordance with one or more embodiments of thepresent disclosure. In one embodiment, system 100 includes a firstcommunication device 101 a, an additional communication device 101 b, abase station device 140, a network 112, a server 120, a controller 114,and a user interface 119. It is noted herein that the descriptionassociated with FIGS. 2 and 5A-5D may also be regarded as applying toFIG. 5E, unless noted otherwise herein.

In one embodiment, system 100 may include a base station device 140.Base station device 140 may include communication circuitry 142 and oneor more processors 144. In one embodiment, base station device 140 mayreceive signals 131, 133 from communication devices (e.g., firstcommunication device 101 a, additional communication device 101 b, andthe like) and transmit network signals 110 to network 112. In thisregard, it is contemplated that base station device 140 may include anydevice which serves as a link in the communication chain betweencommunication devices 101 and network 112. By way of example, a farmoperator implementing system 100 throughout the farm may utilize a basestation device 140 located on top of a barn, fence post, or the like. Itis contemplated herein that the use of a base station device 140 mayprovide a number of advantages to system 100. By way of example, the useof a base station device 140 may serve to improve connectivity betweencommunication devices 101 and network 112. By way of another example,the use of a base station device 140 may allow for lower-powertransmissions from communication devices 101, resulting in smaller, moreefficient communication devices 101.

In one embodiment, the one or more processors 105, 116, 122, 134, 144may include any one or more processing elements known in the art. Inthis sense, the one or more processors 105, 116, 122, 134, 144 mayinclude any microprocessor-type device configured to execute softwarealgorithms and/or instructions. In one embodiment, the one or moreprocessors 105, 116, 122, 134, 144 may consist of a desktop computer,mainframe computer system, workstation, image computer, parallelprocessor, or other computer system (e.g., networked computer)configured to execute a program configured to operate the system 100, asdescribed throughout the present disclosure. It should be recognizedthat the steps described throughout the present disclosure may becarried out by a single computer system or, alternatively, multiplecomputer systems. Furthermore, it should be recognized that the stepsdescribed throughout the present disclosure may be carried out on anyone or more of the one or more processors 105, 116, 122, 134, 144. Ingeneral, the term “processor” may be broadly defined to encompass anydevice having one or more processing elements, which execute programinstructions from memory 107, 118, 124. Moreover, different subsystemsof the system 100 (e.g., first communication device 101 a, additionalcommunication device 101 b, beacon 102, scanner 104, server 120,controller 114, base station device 140) may include processor or logicelements suitable for carrying out at least a portion of the stepsdescribed throughout the present disclosure. Therefore, the abovedescription should not be interpreted as a limitation on the presentdisclosure but merely an illustration.

The memory 107, 118, 124 may include any storage medium known in the artsuitable for storing program instructions executable by the associatedone or more processors 105, 116, 122, 134, 144 and the data receivedfrom the communication devices (e.g., beacons 102, scanners 104). Forexample, the memory 107, 118, 124 may include a non-transitory memorymedium. For instance, the memory 107, 118, 124 may include, but is notlimited to, a read-only memory (ROM), a random access memory (RAM), amagnetic or optical memory device (e.g., disk), a magnetic tape, a solidstate drive and the like. In another embodiment, the memory 107, 118,124 is configured to store data including, but not limited to, entitydata, association data (e.g., spatial relationship data), operationsdata, GPS data, time-stamped data, geo-fenced data, and the likereceived from communication devices (e.g., beacons 102, scanners 104).It is further noted that memory 107, 118, 124 may be housed in a commoncontroller housing with the one or more processors 105, 116, 122, 134,144. In an alternative embodiment, the memory 107, 118, 124 may belocated remotely with respect to the physical location of the processors105, 116, 122, 134, 144, server 120, controller 114, and the like. Inanother embodiment, the memory 107, 118, 124 maintains programinstructions for causing the one or more processors 105, 116, 122, 134,144 to carry out the various steps described through the presentdisclosure.

It is noted that, in the examples described above, a user of system 100may be able to determine a substantial amount of information simply fromanalyzing the time-stamped association (e.g., spatial relationship) andoperation data. For example, by time-stamping the association data, auser may be able to determine when and where a tractor was fueled, andwith which gas tank. Furthermore, if the time-stamped data includedentity information regarding the tractor and gas tank (e.g., tractormake, gas type, gas levels of the tractor and gas tank, and the like), auser may be able to determine if the tractor was fueled using thecorrect fuel, if the fuel taken from the gas tank is equal to the fuelplaced into the tractor, and the like. Furthermore, if a thirdcommunication device was associated with an employee operating thetractor, the time stamped data may also include data regarding theassociation between the user and the tractor. In this regard, a userreviewing the data stored in memory 124 may be able to determine whofueled the tractor.

It is noted that system 100 of the present disclosure may allow a userto more accurately track input cost allocation across smaller landareas. In this regard, the present disclosure may be able to track inputcost allocation down to land areas as small as a square meter orsmaller. The present disclosure may allow for tracking various inventoryincluding, but not limited to, fertilizer, seed, water, pesticide, andthe like.

For example, a tractor may be used to travel throughout a field pullinga sprayer to spray pesticides as needed. The user operating the tractormay have on their person a first scanner 104 a (e.g., cell phone).Further, the tractor may be equipped with a second scanner 104 b and thesprayer may be equipped with a beacon 102. After receiving data vianetwork signals 110 and network 112, the one or more processors 122 mayidentify an association (e.g., spatial relationship) between the user,the tractor, and the sprayer (e.g., between the first scanner 104 a, thesecond scanner 104 b, and the beacon 102). The one or more processors122 may label the three-way association as “Association 1.” The one ormore processors 122 may store Association 1 data in memory 124. AsAssociation 1 continues throughout time and moves through space, the oneor more processors 122 may identify Association 1 as carrying out apesticide spraying operation, and label the operation as “Operation 1.”As Operation 1 continues (e.g., as the tractor pulls the sprayer aroundthe field spraying pesticide), first scanner 104 a and/or second scanner104 b may transmit network signals 110 to network 112, wherein thenetwork signals 110 include multiple data sets including, but notlimited to, time-stamped GPS position data and time-stamped entity data(e.g., data relating to the tractor and sprayer). The time-stampedentity data may include, but is not limited to, the tractor's speed,mileage, fuel level, the sprayer's pesticide level, and the like.

As the tractor travels throughout the field and the sprayer releasespesticides as needed, some areas of the field may require more pesticidethan others. In this regard, pesticide will not be sprayed across theentire field evenly. The data transmitted via network signals 110 mayinclude time-stamped data regarding the tractor's position (e.g., GPSposition of Operation 1) and sprayer pesticide level. In this regard,the present disclosure may be configured to analyze the time-stampeddata in order to determine how the sprayer's pesticide level changedover time/space, therefore determining how much pesticide was used ineach specific area of the field. In one embodiment, the presentdisclosure may be configured to track the pesticide used down to smallincrements of land (e.g., square meter, square half meter, etc.).

It is noted that previous inventory analysis systems and methods may belimited to a field-by-field basis. In this regard, applying this to theprevious example, previous analysis systems and methods may only be ableto determine the amount of pesticide used for an entire field. Incomparison, it is noted that system 100 of the present disclosure mayallow for a more accurate and automated inventory tracking.Additionally, it is noted that tracking inventory and cost allocationdown to smaller land areas through system 100 of the present disclosuremay allow a user to more intelligently and efficiently manage costs andinventory across their entire farmland. The ability of system 100 totrack inventory and cost allocations down to smaller land areas isdepicted in FIG. 6A.

FIG. 6A depicts a portion of a geo-fenced field 600 in which costallocations have been broken down into smaller field subsections 602, inaccordance with one or more embodiments of the present disclosure. Inone embodiment, the geo-fenced field 600 is defined by a pre-definedgeo-fenced boundary 610. In another embodiment, geo-fenced field 600 isbroken into smaller field subsections 602 a, 602 b, 602 m, 602 n, andthe like.

FIG. 6A may be further understood with reference to the previousexample. In this example, a user (e.g., cell phone—first scanner 104)operating a tractor (e.g., second scanner 104 b) may be used to travelthroughout a field pulling a sprayer (e.g., beacon 102) to spraypesticides as needed. System 100 may identify the three-way associationas Association 1 (e.g., user/tractor/sprayer spatial relationship).System 100 may further identify Association 1, as it moves through timeand space, as carrying out a pesticide spraying operation, Operation 1.As noted previously, as Operation 1 continues (e.g., as the tractorpulls the sprayer around the field spraying pesticide), first scanner104 a and/or second scanner 104 b may transmit network signals 110 tonetwork 112, wherein the network signals 110 include multiple data setsincluding, but not limited to, time-stamped GPS position data andtime-stamped entity data (e.g., data relating to the tractor andsprayer). The time-stamped entity data may include, but is not limitedto, the tractor's speed, mileage, fuel level, the sprayer's pesticidelevel, and the like. As the tractor travels throughout the field and thesprayer releases pesticides as needed, some areas of the field mayrequire more pesticide than others. In this regard, pesticide will notbe sprayed across the entire field evenly.

Continuing with the same example, the one or more processors 122 ofserver 120 may be configured to use the change in pesticide level in thesprayer over time and the changing location of Operation 1 over time todetermine how much pesticide was sprayed at each particular locationthroughout the field. The one or more processors 122 may then beconfigured to divide the field up into field subsections 602 such thatthe amount of pesticide used may be divided up by each field subsection602. Furthermore, after determining how much pesticide was used in eachfield subsection 602, the one or more processors 122 may be configuredto use the price of the pesticide to determine the cost of pesticideused per field subsection 602.

In another embodiment, the one or more processors 122 may be configuredto generate a visual representation of the field 600 broken into fieldsubsections 602 depicting the price of pesticide used per fieldsubsection 602. The visual representation may then be displayed on userinterface 119. For instance, referring to FIG. 6A,one or more processors122 may be configured to display that field subsections 602 a, 602 b,602 m, and 602 n required $3.51, $3.55, $2.45, and $3.10 of pesticide,respectively.

Referring again to FIG. 6A, system 100 may be used to generate a visualrepresentation of a field 600 which includes the cost breakdowns of oneor more entities, materials, working hours, and the like. For instance,referring again to the previous example with the pesticide sprayingoperation, the costs depicted in the field subsections 602 of FIG. 6Arepresent only the cost of pesticide used per field subsection 602.However, the one or more processors 122 of server 120 may be configuredto use time-stamped GPS position data and time-stamped entity data(e.g., data relating to the tractor and sprayer) from network signals110 in order to determine many valuation metrics including, but notlimited to, the amount of pesticide used per field subsection 602, theamount of employee time spent per field subsection 602, the amount oftractor run time spent per field subsection 602, the amount of sprayerrun time spent per field subsection 602, and the like.

It is noted that the cost per unit of run time for the tractor andsprayer may be determined using the amortized costs of the tractor andsprayer over their respective lifetimes. In this regard, system 100 maybe configured to generate a visual representation of a field 600 withunit cost breakdowns per field subsection 602, wherein the unit cost perfield subsection includes the cost of pesticide per field subsection602, employee cost per field subsection 602 (e.g., employee timeemployee hourly rate), the running operational cost of the tractor perfield subsection 602, and the running operational cost of the sprayerper field subsection 602. In this regard, instead of FIG. 6A displayingonly the cost of pesticide used per field subsection 602, FIG. 6A mayinstead display the total cost of Operation 1 (e.g., pesticide sprayingoperation) per field subsection 602. This cost allocation breakdown perfield subsection 602 is described in more detail with reference to FIG.6B.

FIG. 6B depicts a portion of a geo-fenced field 600 in which costallocations of a harvesting process have been broken down into fieldsubsections 602, and in which cost allocations have been further brokendown into the various tasks of the harvesting process in graph 620.

As noted previously, system 100 may break down cost allocations perfield subsection 602, and may further break down the cost allocationsper field subsection 602 into the various tasks associated with eachoperation. For example, a “harvesting process” may include many separateoperations throughout a harvesting season, including, but not limitedto, a planting operation, a fertilizing operation, a chemical sprayingoperation, a tilling operation, and the like. Similar to the exampleabove, as each operation moves throughout the field 500, a scanner 104in each operation may transmit network signals 110 to network 112,wherein the network signals 110 include multiple data sets including,but not limited to, time-stamped GPS position data and time-stampedentity data (e.g., data relating to the entities in the operation).Using the time-stamped GPS position data and the time-stamped entitydata, the one or more processors 122 of server 120 may be configured toallocate the cost of each individual task in each operation to eachfield subsection 602 in which that cost was spent.

For instance, one operation in the harvesting process depicted in FIG.6B may be a planting operation in which a user (e.g., first scanner 104a) drives a tractor (e.g., second scanner 104 b) pulling a planter(e.g., beacon 102). The planting operation may be labeled as Operation 1of the entire harvesting process. As Operation 1 moves throughout field600 planting seeds, first scanner 104 a and/or second scanner 104 b maytransmit network signals 110 to network 112, wherein the network signals110 include multiple data sets including, but not limited to,time-stamped GPS position data and time-stamped entity data (e.g., datarelating to the tractor and planter). The time-stamped entity data mayinclude, but is not limited to, the tractor's speed, mileage, fuellevel, the planter's seed level, and the like. As the tractor travelsthroughout the field and the planter plants seeds as needed, some areasof the field may receive more seeds than others. In this regard, seedswill not be laid across the entire field evenly.

Continuing with the same example, the one or more processors 122 ofserver 120 may be configured to use the change in seed level in theplanter over time and the changing location of Operation 1 over time todetermine how much seed was planted at each particular locationthroughout the field. The one or more processors 122 may then beconfigured to divide the field up into field subsections 602 such thatthe amount of seed used may be divided up by each field subsection 602.Furthermore, after determining how much seed was used in each fieldsubsection 602, the one or more processors 122 may be configured to usethe price of the seed to determine the cost of seed used per fieldsubsection 602. Furthermore, the one or more processors 122 of server120 may be configured to use the change in tractor fuel level over timeand the GPS position of Operation 1 over time to determine the amount ofuser time (e.g., salary) and fuel cost expended in each field subsection602.

Continuing with the same example, the process of dividing costallocations up for every task in each operation may be done for eachoperation of the harvesting process. For example, if a harvestingprocess included a seeding operation, a fertilizer operation, a chemicalspraying operation, and a tilling operation, cost allocations for eachoperation may be broken down into each field subsection 602. In thisregard, as shown in graph 620 of FIG. 6B, the cost allocations of theentire harvesting process may be broken down into the cost allocationsfor each field subsection.

It is noted herein that the ability of system 100 to break down costallocations across field subsections 602 may allow for increasedproductivity. For example, referring to FIG. 6B, a user may be able toview the various cost allocations across the various field subsections602 to determine which field subsections 602 require increased cost ascompared to the other field subsections 602. In this example, by viewingthe breakdown of the cost allocations in the field subsection 602 whichcosts more than the others, the user may be able to determine why thatspecific field subsection 602 is costing more than the others. This mayallow the user to take more effective remedial actions in order to bringthe cost of the field subsection 602 down.

FIG. 7A illustrates a first graphical display 700 a depicting a map 702and a corresponding timeline 704, in accordance with one or moreembodiments of the disclosure. In one embodiment, graphical display 700may be displayed on the display device of the user interface 119. In oneembodiment, map 702 of first graphical display 700 a illustrates aconceptual view of a path 701 of a tractor 706 as the tractor 706travels down a road, into a field 710, and pulls an anhydrous ammoniatank 708 (e.g., fertilizing operation). In another embodiment, timeline704 of first graphical display 700 a illustrates various “channels” 705depicting the amount of time the tractor 706 spends traveling in eachstage along its path 701. In this regard, the path 701 of the tractor706 illustrated in map 702 may be broken down into various channels 705as illustrated in timeline 704.

As shown in FIG. 7A, a tractor 706 may begin driving down a road andturn off the road to enter a field 710 (e.g., geo-fenced field 710)along a first path segment 701 a. As shown in the timeline 704 ofgraphical display 700, a first channel 705 a may illustrate the timeperiod the tractor 706 drove down the road and entered the field 710. Inthis regard, first path segment 701 a may correspond to first channel705 a, indicating that the tractor 706 drove for 7 minutes from the timeit started driving to the time it entered the field 710 (e.g., crossedthe geo-fenced boundary of field 710).

FIG. 7B illustrates a second graphical display 700 b depicting a map 702and a corresponding timeline 704, in accordance with one or moreembodiments of the disclosure. As shown in FIG. 7B, a second pathsegment 701 b may be defined as the path 701 of the tractor 706 afterthe tractor 706 crosses the geo-fenced boundary of field 710 andapproaches anhydrous ammonia tank 708. As shown in the timeline 704 ofsecond graphical display 700 b, a second channel 705 b may illustratethe time period the tractor 706 entered the field 710 and approached theanhydrous ammonia tank 708. In this regard, first path segment 701 b maycorrespond to second channel 705 b, indicating that the tractor 706drove for 11 minutes from the time it entered the field 710 to the timeit reached the anhydrous ammonia tank 708 (e.g., entered a spatialrelationship with anhydrous ammonia tank 708).

FIG. 7C illustrates a third graphical display 700 c depicting a map 702and a corresponding timeline 704, in accordance with one or moreembodiments of the disclosure. As shown in FIG. 7C, a third path segment701 c may be defined as the path 701 of the tractor 706 as the tractor706 pulls the anhydrous ammonia tank 708. In this regard, the thirdportion of path 701 c may be defined as the path 701 of the tractor 706during the time the tractor 706 and the anhydrous ammonia tank 708 arein a spatial relationship (e.g., association) and are conducting afertilizing operation throughout field 710.

As shown in the timeline 704 of third graphical display 700 c, a thirdchannel 705 c may illustrate the time period the tractor 706 and theanhydrous ammonia tank 708 conducted the spraying operation in field710. In this regard, the start of third channel 705 c may mark the pointin time in which the tractor 706 and the anhydrous ammonia tank 708formed an association (e.g., spatial relationship). In this regard,third path segment 701 c may correspond to third channel 705 c,indicating that the fertilizing operation has been going on for 3minutes.

FIG. 7D illustrates a fourth graphical display 700 d depicting a map 702and a corresponding timeline 704, in accordance with one or moreembodiments of the disclosure. As shown in FIG. 7D, a fourth pathsegment 701 d may be defined as the path 701 of the tractor 706 afterthe tractor 706 left the anhydrous ammonia tank 708 and traveled towardthe geo-fenced boundary of field 710. In this regard, the fourth pathsegment 701 d may be defined as the path 701 of the tractor 706 afterthe tractor ended the fertilizing operation and exited a spatialrelationship with the anhydrous ammonia tank 708 and traveled toward thegeo-fenced boundary of field 710.

As shown in the timeline 704 of fourth graphical display 700 d, a fourthchannel 705 d may illustrate the time period the tractor 706 traveledtoward the geo-fenced boundary of field 710 after ending the fertilizingoperation and exiting a spatial relationship with the anhydrous ammoniatank 708. In this regard, the start of fourth channel 705 d may mark thepoint in time in which the tractor 706 and the anhydrous ammonia tank708 ended the fertilizing operation and exited a spatial relationshipwith one another. In this regard, fourth path segment 701 d maycorrespond to fourth channel 705 d, indicating that the tractor 706traveled for 15 minutes after ending the fertilizing operation andcrossing the geo-fenced boundary of field 710.

Referring again to FIG. 7D, in one embodiment, system 100 of the presentdisclosure may be configured to mark the last known location of theanhydrous ammonia tank 708 after the fertilizing operation ends and thetractor 706 exits a spatial relationship with the anhydrous ammonia tank708. For example, the tractor 706 may be equipped with a scanner 104,and the anhydrous ammonia tank 708 may be equipped with a beacon 102.When the scanner 104 and the beacon 102 enter a spatial relationship(e.g., association) with one another, the scanner 104 may transmitnetwork signals 110 to network 112, wherein the network signals 110include data regarding the association and the fertilizing operation. Inthis same manner, when the scanner 104 and the beacon 102 (e.g., thetractor 706 and the anhydrous ammonia tank 708) exit a spatialrelationship, scanner 104 may transmit network signals 110 to network112, wherein the network signals 110 include GPS positional data of thelocation of the beacon 102 (e.g., anhydrous ammonia tank 708) when thescanner 104 and the beacon 102 exited the spatial relationship with oneanother. In another embodiment, the GPS positional data of the beacon102 (e.g., anhydrous ammonia tank 708) may be stored in memory 124 ofserver 120.

FIG. 7E illustrates a fifth graphical display 700 e depicting a map 702and a corresponding timeline 704, in accordance with one or moreembodiments of the disclosure. As shown in FIG. 7E, a fifth path segment701 e may be defined as the path 701 of the tractor 706 after thetractor 706 crosses the geo-fenced boundary of field 710 and drives awayfrom the field 710.

As shown in the timeline 704 of fifth graphical display 700 e, a fifthchannel 705 e may illustrate the time period the tractor 706 crossed thegeo-fenced boundary of field 710 and began driving away from the field710. In this regard, the fifth path segment 701 e may correspond tofifth channel 705 e, indicating that the tractor 706 has been travelingfor 3 minutes after crossing the geo-fenced boundary of field 710 anddriving away from the field.

It is noted that the previous examples of graphical displays 700 aregiven merely as an example, and are not to be regarded as limiting. Itis noted herein that the divisions between each of the channels 705(e.g., division between first channel 705 a and second channel 705 b)may indicate any event including, but not limited to, an associationforming, an association ending, an operation beginning, an operationending, a geo-fenced boundary being crossed, and the like.

In one embodiment, the graphical display 700 depicted in FIGS. 7A-7E maybe displayed on any display known in the art including, but not limitedto, a desktop, a monitor, an LCD screen, a touch screen interface, andthe like. In one embodiment, graphical display 700 may be depicted onuser interface 119 of controller 114. It is contemplated that a user mayinteract with graphical display 700 in order to view specific portionsof graphical display 700. For example, if graphical display 700 weredisplayed on user interface 119 with a touch screen display, a user maybe able to slide the timeline 704 to view different time periods. By wayof another example, a user may be able to “zoom” in and out in order toview smaller or larger time periods at a time. It is furthercontemplated that the graphical display 700 depicted in FIGS. 7A-7E mayexhibit additional functional capabilities which facilitate a user'sability to view the information of graphical display 700. For example,additional capabilities of graphical display 700 may include, but arenot limited to, displaying additional information if a user clicks orhovers over each channel of the timeline.

In another embodiment, a user may add and/or edit the informationdisplayed or contained within graphical display 700. For example, imagesand other information may be input manually or automatically via datareceived by scanners 104. It is noted herein that the timeline 704depicted in FIGS. 7A-7E would not only assist a user in reviewing pastevents, but it would also allow the user to easily add and/or editrelevant information such that all the data of system 100 is arranged ina chronological order. For example, a user may desire to add notesrelevant to a certain entity during a particular channel 705. Forinstance, a user may insert a note during the third channel 705 c (e.g.,channel depicting the fertilizing operation) that the tractor 706 wasexperiencing technical difficulties. By way of another example, a usermay input a note that the type of fertilizer being used was changedmid-operation. For example, referring to FIG. 7D, the type of fertilizerbeing used may have been switched half way through the fertilizingoperation depicted by third channel 705 c. In this example a user maydesire to enter this information in on the timeline 704, and could do soby clicking, hovering, or the like, over third channel 705 c on thetimeline 704.

FIG. 8 illustrates a process flow diagram depicting a method 800 fortracking proximity information, in accordance with one or moreembodiments of the present disclosure. It is noted herein that the stepsof method 800 may be implemented all or in part by system 100. It isfurther recognized, however, that the method 800 is not limited to thesystem 100 in that additional or alternative system-level embodimentsmay carry out all or part of the steps of method 800.

In step 802, a first communication device is associated with a firstentity, and an additional communication device is associated with anadditional entity. In one embodiment, the first communication device andthe additional communication device are communicatively couplable. Byway of example, the first communication device may include a beaconassociated with a tractor, and the second communication device mayinclude a scanner associated with a gas tank.

In step 804, a spatial relationship is identified between the firstentity and the additional entity. By way of example, two entities whichare within a specified distance of one another may be said to be in aspatial relationship with one another.

In step 806, an operation unit defined by an association between thefirst entity and the additional entity is identified based on thespatial relationship between the first entity and the additional entity.For example, when a spatial relationship between a tractor and a gastank is identified over a period of time, the present disclosure mayidentify the spatial relationship as a fueling operation.

In step 808, a geo-fenced area is defined. By way of example, ageo-fenced area may be defined by a series of GPS coordinates, or may bedefined as a region relative to a particular entity. For instance, auser may define the outer perimeter of a field as a first geo-fencedboundary defining a first geo-fenced area.

In step 810, it is determined whether the operation unit is within thedefined geo-fenced area.

In step 812, one or more location-based characteristics of the operationunit are determined based on the determination of the operation unitwithin the defined geo-fenced area and one or more characteristics ofoperation unit. Location-based characteristics may include, but are notlimited to, the amount of seed planted in particular areas, the amountof fertilizer used in particular area, the fuel type and fuel level of atractor based on the location of a fueling operation (e.g., adjacent toa fuel tank), and the like.

In step 814, one or more characteristics of the operation unit arestored in memory.

In step 816, the one or more characteristics of the operation unit arereported via a user interface. By way of example, a user interface maydisplay the seed allocations throughout a field, employee hours brokendown by operation unit, and the like. It is contemplated that a user mayutilize the displayed information (e.g., reported one or morecharacteristics) to perform one or more tasks, or adjust one or moreoperating parameters in response to the reported information. By way ofexample, a farm owner may reconcile fuel usage, reconcile employeehours, alter fertilization, seed, or irrigation allocations throughoutthe farm, and the like.

FIGS. 9-19 generally illustrate graphical user interfaces for providingproximity-based analysis, in accordance with one or more embodiments ofthe present disclosure. It is contemplated herein that the graphicaluser interfaces depicted in FIGS. 9-19 may illustrate one or moreembodiments, elements, statistics, spatial relationships, or operationsof the present disclosure. In this regard, it is contemplated that thegraphical user interfaces depicted in FIGS. 9-19 may illustrate and/ordisplay any data collected and/or analyzed by the present disclosure. Itis further noted, however, that the graphical user interfaces depictedin FIGS. 9-19 are for illustrative purposes only, and are not to beregarded as a limitation on the scope of the present disclosure.

It is contemplated herein that the graphical user interfaces depicted inFIGS. 9-19 may be displayed on one or more components of the presentdisclosure. By way of example, the graphical user interfaces depicted inFIGS. 9-19 may be displayed on one or more communication devices 101and/or user interface 119 of system 100. In this regard, a user mayview, filter, edit, and modify one or more characteristics of system 100in response to the displayed graphical user interfaces depicted in FIGS.9-19.

FIG. 9 illustrates a graphical user interface 900 for providingproximity-based analysis, in accordance with one or more embodiments ofthe present disclosure.

In one embodiment, graphical user interface 900 illustrates a list ofentities being tracked by system 100. In one embodiment, a user mayfilter the list of tracked entities by entity name/type (e.g.,“equipment”), geo-fenced area (e.g., “fence”), operation, spatialrelationship, and the like. In another embodiment, a user may usegraphical user interface 900 to search for a particular entity.

FIG. 10 illustrates a graphical user interface 1000 for providingproximity-based analysis, in accordance with one or more embodiments ofthe present disclosure.

In one embodiment, graphical user interface 1000 illustrates a reportgenerated for an entity (e.g., “entity report”). In one embodiment, anentity report may include, but is not limited to, total cost, ownershipcost, hourly operating cost, percent utilization over time, and thelike. In another embodiment, a user may be able to filter the entityreport using one or more filters including, but not limited to, date,time, operation, geo-fenced area (e.g., “field”), and the like.

FIG. 11 illustrates a graphical user interface 1100 for providingproximity-based analysis, in accordance with one or more embodiments ofthe present disclosure.

In one embodiment, graphical user interface 1100 illustrates a reportgenerated for an employee associated with system 100 (e.g., “employeereport” or “operator report”). In one embodiment, an operator report mayinclude, but is not limited to, the total hours worked by the employee,the hourly rate of the employee, the total amount owed to the employee,the average hours worked by the employee, and the like. In anotherembodiment, a user may be able to filter the operator report using oneor more filters including, but not limited to, date, time, operation,geo-fenced area (e.g., “field”), and the like.

FIG. 12 illustrates a graphical user interface 1200 for providingproximity-based analysis, in accordance with one or more embodiments ofthe present disclosure.

In one embodiment, graphical user interface 1200 illustrates a reportgenerated for an operation tracked by system 100 (e.g., “operationreport”). In one embodiment, an operation report may include, but is notlimited to, the total hours spent on the operation, the hourly operatingcost for the operation, the total cost of the operation, the averagetime spent per day on the operation, the operating cost for theoperation per acre and/or other land area, and the like. In anotherembodiment, a user may be able to filter the operation report using oneor more filters including, but not limited to, date, time, equipmentused (e.g., entity used), geo-fenced area (e.g., “field”), and the like.

FIG. 13 illustrates a graphical user interface 1300 for providingproximity-based analysis, in accordance with one or more embodiments ofthe present disclosure.

In one embodiment, graphical user interface 1300 illustrates a map viewof one or more geo-fenced areas of system 100 (e.g., “map view”). In oneembodiment, a map view may include, but is not limited to, the perimeterof one or more geo-fenced areas, the location of one or more entitieslocated within the one or more geo-fenced areas, the identity of one ormore entities located within the one or more geo-fenced areas,operations, spatial relationships, and the like. In another embodiment,a user may be able to select one or more displayed geo-fenced areas,entities, spatial relationships, operations, and the like, in order toview one or more characteristics of the selected item. By way ofexample, as illustrated in FIG. 13, if a user selected an entity that isa grain bin, graphical user interface 1300 may display one or morecharacteristics of the entity (e.g., the grain bin), including, but notlimited to, the fill level, the date of the last full level, and thelike. In this regard, the map view may include information regardingstored inputs and outputs of various operations. In another embodiment,graphical user interface 1300 may be toggled between one or more viewsincluding, but not limited to, a satellite view, a topographic view, andthe like.

FIG. 14 illustrates a graphical user interface 1400 for providingproximity-based analysis, in accordance with one or more embodiments ofthe present disclosure.

In one embodiment, graphical user interface 1400 illustrates a graphicaluser interface which may be particularly compatible with portableelectronic devices including, but not limited to, smartphones, tablets,and the like. In one embodiment, graphical user interface 1400 mayillustrate a screen which may prompt a user to start and/or stoptracking one or more entities of system 100. In another embodiment, asdepicted in FIG. 14, a user may be able to view active devices, selectequipment that has been assigned to a communication device 101, connecta beacon 102 or other communication device 101, and the like.

FIG. 15 illustrates a graphical user interface 1500 for providingproximity-based analysis, in accordance with one or more embodiments ofthe present disclosure.

In one embodiment, graphical user interface 1500 illustrates a menuwhich may allow a user to effectively and efficiently view, select, andmodify one or more embodiments of system 100.

FIG. 16 illustrates a graphical user interface 1600 for providingproximity-based analysis, in accordance with one or more embodiments ofthe present disclosure.

In one embodiment, graphical user interface 1600 illustrates a setupgraphical user interface which may allow a user to assign entities toassociated communication devices 101. In one embodiment, graphical userinterface 1600 may be displayed when system 100 is scanning for nearby“available” communication devices 101 which have not been previouslyassigned to an entity. In another embodiment, graphical user interface1600 may display “available” communication devices 101, which may thenbe selected and assigned to a particular entity.

FIG. 17 illustrates a graphical user interface 1700 for providingproximity-based analysis, in accordance with one or more embodiments ofthe present disclosure.

In one embodiment, graphical user interface 1700 illustrates an overheadview of at least a portion of system 100. In one embodiment, graphicaluser interface 1700 may illustrate one or more embodiments of system 100including, but not limited to, the current location of a user, one ormore geo-fenced areas, one or more entities, one or more operations, andthe like. In another embodiment, a user may be able to select one ormore displayed geo-fenced areas, entities, spatial relationships,operations, and the like, in order to view one or more characteristicsof the selected item. In another embodiment, graphical user interface1300 may be toggled between one or more views including, but not limitedto, a satellite view, a topographic view, and the like.

FIG. 18 illustrates a graphical user interface 1800 for providingproximity-based analysis, in accordance with one or more embodiments ofthe present disclosure.

In one embodiment, graphical user interface 1800 illustrates a menudepicting entities (e.g., “atoms”) which are being tracked by system100. In one embodiment, graphical user interface 1800 may includethumbnails or other pictures depicting each atom displayed. In anotherembodiment, graphical user interface 1800 may illustrate a status symbolfor each atom displayed. By way of example, a “check” status icon, asillustrated in FIG. 18, may indicate that there are no detected issueswith the atom. By way of another example, an “X” status icon mayindicate that there are one or more identified issues with the item,indicating that action must be taken with respect to the atom. Inanother embodiment, a user may filter the atoms displayed on graphicaluser interface 1800.

FIG. 19 illustrates a graphical user interface 1900 for providingproximity-based analysis, in accordance with one or more embodiments ofthe present disclosure.

In one embodiment, graphical user interface 1900 illustrates a detailedreport of an atom. In one embodiment, graphical user interface 1900 mayresult following a user selecting an atom displayed in graphical userinterface 1800. In one embodiment, graphical user interface 1900includes a map view illustrating the location of the atom. In anotherembodiment, graphical user interface 1900 displays one or more metricsassociated with the atom including, but not limited to, the status iconof the atom, the GPS location of the atom, the current operating hoursof the atom, the operating cost per hour of the atom, and the like.

EXAMPLES

The numerous advantages of the present disclosure may be betterunderstood with reference to multiple examples. In this regard, thefollowing examples are provided to assist those skilled in the art tobetter understand the numerous advantages of the present disclosure, andare not to be understood as limiting.

Example 1: Allocation of Input Costs (e.g., Tillage, Fertilizer, etc.)

In a first example, a farm administrator may wish to reconcile tillage,fertilizing, planting, and harvesting costs against fields at the end ofthe planting season. Ordinarily, the administrator begins by pullingreports from geo-locations and layers software such as John Deere's Apexor AgLeader's SMS Advanced. These reports show information that wassuccessfully recorded by the tractors' on-board monitors. It isexceedingly expensive to place on-board monitors on every piece ofequipment. Thus, some equipment does not have an on-board monitor,causing the data associated with the operation of these pieces ofequipment to be missed. For example, if a sprayer were not equipped withan on-board monitor, the costs associated with operating the sprayerwould not be recorded. Based on the information received from theavailable on-board monitors, the administrator estimates the cost of allthe operations and spreads those estimates evenly across the fields.However, because not all equipment was tracking data with on-boardmonitors, this estimate may be highly inaccurate. Additionally,spreading the costs evenly across every field may not accurately displaythe actual costs associated with each field. Furthermore, since not alloperators enter their names into the equipment of the on-board monitorwhen they start a particular operation, the administrator evenly spreadstheir salary for the planting season across those fields. Once again,because operators were not able to enter their names into the equipmentwithout an on-board monitor, the operator time data may be skewed. Theadministrator generates a report based on the data from all the on-boardmonitors. Although the administrator knows the data is not completelyaccurate, there is no way of improving its accuracy with the currentstate of the equipment and budget.

It is noted herein that utilizing various embodiments of the presentdisclosure may improve the reconciliation of tillage, fertilizing,planting, and harvesting costs at the end of the year. Prior to startingthe season, the administrator may install transmitting devices (e.g.,communication devices 101, scanners 104, beacons 102) on variousentities, which would be used throughout the year (e.g., tractor,implement, combine, sprayer, pickup, tanks, and the like). Each fieldmay also be geo-fenced prior to the season. Furthermore, each operatorof the administrator's team is equipped with a mobile device, such as acell phone (e.g., scanner 104) having a Bluetooth/WiFi connection, whilethey are working. Throughout the course of the planting season, softwareon each operator's device (e.g., scanner 104) receives signals frombeacons 102 it came close to and indexes the data received from beacons102 with a GPS position and time. The operator's phone (e.g., scanner)then stores the data in memory. When the phone regains a networkconnection, it transmits the stored data to a server 120 via network112. At the time of reconciliation, the administrator may access thedata stored on server 120 via user interface 119 of controller 114. Dueto the fact that the fields were geo-located and the scanners 104tracked the location of each operation, the processors of the server 120and/or controller 114 are able to associate operations and operator timeto the appropriate geo-located fields and/or field subsections 502. Asimple report, customized to the cooperation's needs is generated. Costscan be tracked to the field subsection 602 in a particular field forwhich the cost was spent.

Example 2: Allocation of Fuel Costs

In a second example, a farm operator may pull a tractor up to dieseltank in farm yard with the intention to fuel the tractor. After theoperator fills the tank to the desired level, the operator writes downthe amount of fuel used for that specific tractor in a notebook locatednear the diesel pump. Once a month, the farm bookkeeper transcribes themanual fuel entries into bookkeeping software for the farm. It is notpossible to track the fuel used to specific fields or implements becauseit is likely that multiple implements have been utilized per tractorover a single fuel filling period. Furthermore, because some operatorsare not diligent in recording the amount of fuel used after each fill,the fuel usage records are not accurate.

It is noted herein that utilizing various embodiments of the presentdisclosure may improve fuel cost reconciliation and allocation. By wayof example, the farm operator may pull a tractor up to fuel tank in farmyard with the intention to fuel the tractor. The tractor is equippedwith a scanner 104 and the fuel tank is equipped with a beacon 102. Boththe scanner 104 and the beacon 102 are configured to receive andtransmit entity data (e.g., tractor speed, tractor fuel level, fuel tankfuel level, and the like). Furthermore, the scanner 104 is configureddetermine the tractor's GPS position and transmit the GPS position. Asthe operator pulls the tractor near the fuel tanks, a scanner 104 on thetractor receives signals from the beacon 102 on the tank. The scanner104 detects a spatial relationship between the scanner 104 and thebeacon 102, thereby forming an association. As the fuel nozzle from thefuel tank is “undocked” from its cradle, the beacon 102 transmits thetank fuel level to the scanner 104 (e.g., beginning fuel level). Oncethe fuel nozzle “re-docks” into its cradle, the beacon 102 againtransmits the tank fuel level to the scanner 104 (e.g., ending fuellevel). After the fueling operation is completed, the scanner 104 thentransmits the beginning and ending tank fuel levels to a server 120 vianetwork 112. The beginning and ending tank fuel levels, as well as thedifference between the two (e.g., amount of fuel withdrawn) is stored inmemory.

As the tractor performs a task throughout a field, the scanner 104transmits network signals 110 to server 120 via network 112, wherein thenetwork signals 110 includes multiple time-stamped data streamsincluding GPS positional data, tractor speed, tractor fuel level,tractor fuel efficiency, and the like. One or more processors 122 ofserver 120 use the data from network signals 110, including the GPSposition of the tractor and the tractor fuel level, in order todetermine the amount of fuel consumed across each field subsection 602.In this regard, fuel consumption and fuel cost is able to be broken downinto small field areas (e.g., field subsections 602) to account forvariable costs across small field increments. Once the fuel consumptiondata is reconciled, the resulting data may be stored in memory 124 or aremote cloud-based farm bookkeeping software.

By way of another example, if the scanner 104 detected a spatialrelationship with a beacon 102 equipped to a fuel tank with theincorrect fuel for the tractor, a warning would be produced. The one ormore processors 122 may cause the server 120 to transmit a warning tothe tractor operator's phone (e.g., second scanner 104 b) in order toalert the operator and to prevent filling the tractor with the incorrectfuel. These warnings may prevent fuel waste as well as prevent damagingequipment.

Example 3: Grain Transport Logistics

In a third example, a truck driver may pick up a load of grain from acombine and haul the load to a grain elevator. Due to the high volume oftrucks that are hauling grain to the elevator, there is a long wait lineat the elevator. Thus, the truck driver may waste a significant amountof his day because he has no way to know how long the line at the grainelevator will be.

It is noted herein that utilizing various embodiments of the presentdisclosure may allow for improved time management and efficiency. By wayof example, the same truck driver may pick up a load of grain from acombine and haul the load to a grain elevator. All the farmers in thearea have equipped their trucks with scanners 104 a. Furthermore, thegrain elevator is equipped with a scanner 104 b. As trucks pull up tothe grain elevator, scanners 104 a and scanner 104 b detect a spatialrelationship, and transmit the time-stamped spatial relationship to aserver 120. Based on the number of trucks at the elevator (e.g., numberof trucks in a spatial relationship with the elevator), one or moreprocessors 122 of the server 120 may be configured to calculate theamount of time it will take for all the trucks to deposit their grain(e.g., wait time). Prior to planning his trip, the truck driver logsonto his smart phone app to access the data stored on server 120 inorder to determine length of the line and the wait time at severalelevators. The truck driver's smart phone app recommends delivering thegrain to the elevator with the shortest wait time

In another embodiment, the one or more processors 122 of the server 120may make grain elevator recommendations to truck drivers based on thewait time at each elevator as well as the distance to each elevator. Forexample, the elevator with the shortest wait time may be the farthestone away, and therefore not be the fastest. In this case, the one ormore processors 122 may recommend the grain elevator which will have theshortest overall time (e.g., wait time plus drive time).

Example 4: Automatic Reconciliation of Equipment Pairing

In a fourth example, a forage harvester may drive up to hook up to aspecific header. The operator must select several values in thevehicle's terminal in order to match the specific width and type ofheader. Because these values must be selected manually, the operatoroccasionally selects the incorrect values, resulting in equipmentdamage.

It is noted herein that utilizing various embodiments of the presentdisclosure may allow a harvester to more efficiently pair equipment andprevent equipment damage. By way of example, the same forage harvestermay drive up to hook up to a specific header. The harvester is equippedwith a scanner 104, and the header is equipped with a beacon 102. Oncethe forage harvester comes within a certain distance of the header,scanner 104 identifies a spatial relationship with beacon 102. When thespatial relationship between the scanner 104 and the beacon 102 for acertain length of time, the forage harvester settings (e.g., width andtype of header) automatically change. In the case that multiple headersare in a spatial relationship with the forage harvester, the forageharvester settings may adjust corresponding to the harvester with thestrongest wireless connection with the scanner 104. Due to the fact thatwireless connection may be inversely proportional to distance, adjustingthe forage harvester settings to correspond with the strongestconnection is likely adjusts the forage harvester to the nearest header.

It is contemplated that this automatic reconciliation of equipmentpairing may help ensure that the automatic reconciliation of costs willbe allocated to the correct agricultural entity. It is furthercontemplated that automatic reconciliation of equipment pairing maypoke-yoke the bookkeeping system to ensure costs are allocated to thecorrect entity. For example, if user recorded that a 24-row planter wasused instead of the correct 16-row planter that was actually used, thecosts could be incorrectly applied. With automatic reconciliation ofequipment pairing, these mistakes may be minimized to ensure accuratecost allocations.

Example 5: Automatic Reconciliation of Agricultural Inputs (Seed)

In a fifth example, a planter box may be filled with the wrong seed.Using current technology, there is no solution to prevent filling theplanter box with the wrong seed. In addition, there is no automaticmethod for automatically assigning the respective costs of the variousseeds to specific areas of a field.

It is noted herein that utilizing various embodiments of the presentdisclosure may prevent m is-allocating agricultural products. By way ofexample, a planter may be equipped with a scanner 104, and a seedcontainer may be equipped with a beacon 102. As the seed container isbrought into close proximity with the planter, the scanner 104 receivessignals from beacon 102 and identifies a spatial relationship betweenthe planter and the seed container. If the seed container contains theincorrect type of seed for the planter, system 100 may provide an alertto a user's phone informing the user that the incorrect type of seed mayabout to be used. In this regard, system 100 may prevent filling theplanter with the wrong seed.

Additionally, as the planter travels throughout a field, system 100 maybe configured to track seed allocation costs across different fieldsand/or field subsections 602. Furthermore, system 100 may generatealerts to ensure that the correct seed types are being planted in thecorrect location based (e.g., correct field, correct soil type, etc.).

Example 6: Automatic Reconciliation of Agricultural Inputs (Herbicide)

In a sixth example, a sprayer may be filled with an incorrect type ofherbicide/pesticide. Using current technology, there is no solution toprevent filling the sprayer with the wrong chemical. Additionally,filling a sprayer with the incorrect type of chemical may lead to inputcost waste, equipment damage, and crop damage. Furthermore, usingcurrent technology, there is no way to automatically trackherbicide/pesticide allocation across particular fields.

It is noted herein that utilizing various embodiments of the presentdisclosure may prevent m is-allocating agricultural inputs. By way ofexample, the sprayer may be equipped with a scanner 104, and theherbicide container may be equipped with a beacon 102. As the herbicidecontainer is brought into close proximity with the sprayer, the scanner104 receives signals from beacon 102 and identifies a spatialrelationship between the sprayer and the herbicide container. If theherbicide container contains the incorrect type of herbicide for thesprayer, system 100 may provide an alert to a user's phone informing theuser that the incorrect type of herbicide may about to be used.

Additionally, as the sprayer travels throughout a field, system 100 maybe configured to track herbicide allocation costs across differentfields and/or field subsections 602. Furthermore, system 100 maygenerate alerts to ensure that the correct herbicide type is being usedin the correct location based (e.g., correct field, correct soil type,etc.). In this regard, system 100 may help to ensure the application ofthe right chemicals to maximize the highest possible overall profit perfarmed area.

Example 7: Automatic Prediction of Real-Time Inventory Discrepancies(Theft Prevention)

In a seventh example, a farm employee may intend to steal valuablechemicals from the farm. The farm employee drives a pickup filled withthe chemicals out of the farm yard and begins driving down the road. Thefarm owner has no immediate way of knowing the chemicals have beenstolen until the chemicals come up missing at the time of inventorycycle counting.

It is noted herein that utilizing various embodiments of the presentdisclosure may allow for real-time inventory discrepancy notificationand prevent theft. By way of example, the same farm employee may intendto steal valuable chemicals from the farm. The employee's truck may beequipped with a scanner 104, and the chemical containers may be equippedwith a beacon 102. The farm operator again drives the truck filled withthe chemicals out of the farm yard and begins driving down the road.Ordinarily, truck and/or the chemical containers would not be operatingin this area or down this route.

As the truck drove away, scanner 104 transmitted GPS positional data andentity data (e.g., truck speed, truck/chemical container spatialrelationship data, and the like) to server 120 via network 112. As thetruck crossed the pre-defined geo-fenced boundary of the farm yard,system 100 identified that the truck (e.g., scanner 104) had left thefarm yard with the chemical container (e.g., beacon 102) down a route itwould not normally operate. Once system 100 detects the truck and thechemical containers traveling down a route it would otherwise notoperate (due to any factors, including the physical route taken, time ofday, and the like), one or more processors 122 of server 120 maytransmit an alert to a user interface 119 notifying the farm owner ofthe potential problem.

Example 8: Automatic Reconciliation of Agricultural Deliveries (LiveCommodities)

In an eighth example, a truck driver may deliver a load of swine to apacking plant. Using current technology, it is typically necessary tomanually record the load via bookkeeping software to reconcile theresulting payment to the delivery. It is generally also not possible toautomatically associate a specific animal to a specific delivery to thepacker.

It is noted herein that utilizing various embodiments of the presentdisclosure may allow for automatic reconciliation of agriculturaldeliveries, including live commodities. By way of example, the truckdriver may prepare to deliver a load of swine to a packing plant. Here,the truck is equipped with a first scanner 104 a, the loading chute isequipped with a second scanner 104 b, and each hog is equipped with anear tag (e.g., ear tag beacon 102). As the hogs are being loaded intothe truck via the loading chute, the second scanner 104 b on the loadingchute identifies each hog (via ear tag beacons 102) as they pass throughthe loading chute into the truck. The second scanner 104 b on theloading chute transmits a unique hog identifier corresponding to eachear tag beacon 102 as well as the loading time of each hog to server 120via network 112. Additionally, one or more processors 122 of server 120may be configured to associate each hog (via unique hog identifier) to aparticular chute number, pen number, truck number, truck driver, and thelike.

When the truck delivers the load to the packing facility, the secondscanner 104 b on the loading chute identifies each hog (via ear tagbeacons 102). The second scanner 104 b on the loading chute transmitsthe unique hog identifier, chute number, pen number, unloading time, andthe like to server 120 via network 112. In this regard, system 100 maybe used to automatically correlate a specific load and specific hogs toa specific packing plant payment or delivery invoice. Furthermore, itwould be possible to automatically associate a truck driver, fuel usage,transport time, etc. to a specific load.

Continuing with the same example, system 100 may be configured toidentify inconsistencies and inefficiencies. For example, if scanner 104b tracked transmitted the weight of each hog as the hog was loaded ontothe truck (e.g., start weight), and transmitted the weight of each hogas the hog was unloaded at the packing facility (e.g., end weight),system 100 may be configured to determine hog shrinkage. In this regard,system 100 may be configured to determine that a specific truck driverhas been inhumane when unloading the hogs that he transports (i.e. heconsistently has shrink of 2.5 hogs/load compared to other truck driverswhose shrink is 0.75/load). Trends like this are often not obviousunless data analytics are utilized. Furthermore, with this system, itwould be possible to track animals along the value chain; all the wayback to their origin.

Example 9: Automatic Reconciliation of Agricultural Deliveries (GrainCommodities)

In a ninth example, a truck driver may deliver a load of corn to anelevator or cooperative. Using current technology, it is typicallynecessary to manually record the load via bookkeeping software toreconcile the load with the resulting payment to the farm. It isgenerally not possible to automatically associate a specific load to aspecific delivery to the packer.

It is noted herein that utilizing various embodiments of the presentdisclosure allow for automatic reconciliation of agriculturaldeliveries, including grain commodities. By way of example, the truckdriver may prepare to deliver a load of corn to an elevator orcooperative. Here, the conveyor is equipped with a first scanner 104 a,the truck is equipped with a second scanner 104 b, and one or morebeacons 102 are placed in the corn. The one or more beacons 102 in thecorn may include sensors which collect data including, but not limitedto, moisture levels, fungus, insect history, and the like. As the cornis loaded into the truck, first scanner 104 a on the conveyor identifiesthe one or more beacons 102 in the corn. The first scanner 104 a on theconveyor transmits unique grain identifiers (e.g., beacon 102identifiers) linking the corn to its origin, loading time, and healthparameters (e.g., moisture levels and the like) to server 120 vianetwork 112. In this regard, one or more processors 122 of server 120may be configured to associate corn identifiers with loading time, trucknumber, bin number, truck driver, commodity history, and the like.

When the truck delivers the load to the elevator or cooperative, ascanner 104 on the unloading receptacle (e.g., pit, dump conveyor, etc.)may identify each beacon 102 in the corn. Scanner 104 may then transmitthe unique grain identifiers (e.g., beacon 102 identifiers), unloadingtime, truck number, truck driver, pit number, and the like. In thisregard, system 100 may be configured to automatically correlate aspecific load to a specific packing plant payment or truck invoice,thereby enabling a user to track the grain back to its origin.

Continuing with the same example, system 100 may be configured toautomatically associate a truck driver, fuel usage, transport time, etc.to a specific load. Furthermore, system 100 may be configured todetermine that a specific truck driver has siphoned off a small portionof grain per load prior to making a delivery. For example, if beacons102 in a load of corn end up being delivered to an elevator through aquestionable customer delivery which was not intended, system 100 may beconfigured to transmit an alert to the farm owner. It is noted hereinthat such an inconsistency would only be noticeable when this data canbe compared between a specific customer and information captured at boththe origin and delivered locations.

Those having skill in the art will appreciate that there are variousvehicles by which processes and/or systems and/or other technologiesdescribed herein can be effected (e.g., hardware, software, and/orfirmware), and that the preferred vehicle will vary with the context inwhich the processes and/or systems and/or other technologies aredeployed. For example, if an implementer determines that speed andaccuracy are paramount, the implementer may opt for a mainly hardwareand/or firmware vehicle; alternatively, if flexibility is paramount, theimplementer may opt for a mainly software implementation; or, yet againalternatively, the implementer may opt for some combination of hardware,software, and/or firmware. Hence, there are several possible vehicles bywhich the processes and/or devices and/or other technologies describedherein may be effected, none of which is inherently superior to theother in that any vehicle to be utilized is a choice dependent upon thecontext in which the vehicle will be deployed and the specific concerns(e.g., speed, flexibility, or predictability) of the implementer, any ofwhich may vary.

All of the methods described herein may include storing results of oneor more steps of the method embodiments in memory. The results mayinclude any of the results described herein and may be stored in anymanner known in the art. The memory may include any memory describedherein or any other suitable storage medium known in the art. After theresults have been stored, the results can be accessed in the memory andused by any of the method or system embodiments described herein,formatted for display to a user, used by another software module,method, or system, and the like. Furthermore, the results may be stored“permanently,” “semi-permanently,” temporarily,” or for some period oftime. For example, the memory may be random access memory (RAM), and theresults may not necessarily persist indefinitely in the memory.

It is further contemplated that each of the embodiments of the methoddescribed above may include any other step(s) of any other method(s)described herein. In addition, each of the embodiments of the methoddescribed above may be performed by any of the systems described herein.

One skilled in the art will recognize that the herein describedcomponents (e.g., operations), devices, objects, and the discussionaccompanying them are used as examples for the sake of conceptualclarity and that various configuration modifications are contemplated.Consequently, as used herein, the specific exemplars set forth and theaccompanying discussion are intended to be representative of their moregeneral classes. In general, use of any specific exemplar is intended tobe representative of its class, and the non-inclusion of specificcomponents (e.g., operations), devices, and objects should not be takenlimiting.

The herein described subject matter sometimes illustrates differentcomponents contained within, or connected with, other components. It isto be understood that such depicted architectures are merely exemplary,and that in fact many other architectures can be implemented whichachieve the same functionality. In a conceptual sense, any arrangementof components to achieve the same functionality is effectively“associated” such that the desired functionality is achieved. Hence, anytwo components herein combined to achieve a particular functionality canbe seen as “associated with” each other such that the desiredfunctionality is achieved, irrespective of architectures or intermedialcomponents. Likewise, any two components so associated can also beviewed as being “connected,” or “coupled,” to each other to achieve thedesired functionality, and any two components capable of being soassociated can also be viewed as being “couplable,” to each other toachieve the desired functionality. Specific examples of couplableinclude but are not limited to physically mateable and/or physicallyinteracting components and/or wirelessly interactable and/or wirelesslyinteracting components and/or logically interacting and/or logicallyinteractable components.

Furthermore, it is to be understood that the invention is defined by theappended claims. It will be understood by those within the art that, ingeneral, terms used herein, and especially in the appended claims (e.g.,bodies of the appended claims) are generally intended as “open” terms(e.g., the term “including” should be interpreted as “including but notlimited to,” the term “having” should be interpreted as “having atleast,” the term “includes” should be interpreted as “includes but isnot limited to,” and the like). It will be further understood by thosewithin the art that if a specific number of an introduced claimrecitation is intended, such an intent will be explicitly recited in theclaim, and in the absence of such recitation no such intent is present.For example, as an aid to understanding, the following appended claimsmay contain usage of the introductory phrases “at least one” and “one ormore” to introduce claim recitations. However, the use of such phrasesshould not be construed to imply that the introduction of a claimrecitation by the indefinite articles “a” or “an” limits any particularclaim containing such introduced claim recitation to inventionscontaining only one such recitation, even when the same claim includesthe introductory phrases “one or more” or “at least one” and indefinitearticles such as “a” or “an” (e.g., “a” and/or “an” should typically beinterpreted to mean “at least one” or “one or more”); the same holdstrue for the use of definite articles used to introduce claimrecitations. In addition, even if a specific number of an introducedclaim recitation is explicitly recited, those skilled in the art willrecognize that such recitation should typically be interpreted to meanat least the recited number (e.g., the bare recitation of “tworecitations,” without other modifiers, typically means at least tworecitations, or two or more recitations). Furthermore, in thoseinstances where a convention analogous to “at least one of A, B, and C,and the like” is used, in general such a construction is intended in thesense one having skill in the art would understand the convention (e.g.,“a system having at least one of A, B, and C” would include but not belimited to systems that have A alone, B alone, C alone, A and Btogether, A and C together, B and C together, and/or A, B, and Ctogether, and the like). In those instances where a convention analogousto “at least one of A, B, or C, and the like” is used, in general such aconstruction is intended in the sense one having skill in the art wouldunderstand the convention (e.g., “ a system having at least one of A, B,or C” would include but not be limited to systems that have A alone, Balone, C alone, A and B together, A and C together, B and C together,and/or A, B, and C together, and the like). It will be furtherunderstood by those within the art that virtually any disjunctive wordand/or phrase presenting two or more alternative terms, whether in thedescription, claims, or drawings, should be understood to contemplatethe possibilities of including one of the terms, either of the terms, orboth terms. For example, the phrase “A or B” will be understood toinclude the possibilities of “A” or “B” or “A and B.”

It is believed that the present disclosure and many of its attendantadvantages will be understood by the foregoing description, and it willbe apparent that various changes may be made in the form, constructionand arrangement of the components without departing from the disclosedsubject matter or without sacrificing all of its material advantages.The form described is merely explanatory, and it is the intention of thefollowing claims to encompass and include such changes. Furthermore, itis to be understood that the invention is defined by the appendedclaims.

What is claimed:
 1. A system comprising: a first communication deviceassociated with a first entity; an additional communication deviceassociated with an additional entity; a database; one or more processorscommunicatively coupled to at least one of the first communicationdevice or the at least an additional communication device, wherein theone or more processors are configured to: identify a spatialrelationship between the first entity and the additional entity based onone or more signals from the first communication device or one or moresignals from the additional communication device; identify an operationunit defined by an association between the first entity and theadditional entity based on the spatial relationship between the firstentity and the additional entity, wherein the operation unit comprises acombination of the first entity and the additional entity, wherein theidentification of the operation unit is triggered by an identificationof a distance, below a threshold distance, between the firstcommunication device associated with the first entity and the additionalcommunication device associated with the additional entity, wherein thefirst entity comprises a first device and the additional entitycomprises at least one of an additional device or a person; determinewhether the operation unit is positioned within a defined geo-fencedarea; determine one or more characteristics of the operation unit basedon the determination of the operation unit within the defined geo-fencedarea; store the one or more characteristics of the operation unit in thedatabase; and report the one or more characteristics of the operationunit via a user interface.
 2. The system of claim 1, wherein the one ormore processors are further configured to provide an alert to a user viathe user interface regarding the one or more location-basedcharacteristics of the operation unit.
 3. The system of claim 1, whereinat least one of the first communication device or the additionalcommunication device comprises a scanner.
 4. The system of claim 1,wherein the first communication device comprises a scanner and theadditional communication device comprises a beacon.
 5. The system ofclaim 1, wherein the additional communication device comprises two ormore communication devices and the additional entity comprises two ormore entities.
 6. The system of claim 5, wherein a second communicationdevice is associated with a second entity, and a third communicationdevice is associated with a third entity.
 7. The system of claim 1,wherein at least one of the first entity or the additional entity ismoveable.
 8. The system of claim 7, wherein at least one of the firstentity or the additional entity comprises at least one of a vehicle or afarming implement.
 9. The system of claim 8, wherein at least one of thefirst entity or the additional entity comprises at least one of atractor, a combine, a trailer, a cart, tillage equipment, a sprayer, aplanter, harvester.
 10. The system of claim 1, wherein at least one ofthe first entity or the additional entity is stationary.
 11. The systemof claim 10, wherein at least one of the first entity or the additionalentity comprises a fuel tank, a water tank, a seed container, a chemicalcontainer, or a building.
 12. The system of claim 1, wherein at leastone of the first entity or the additional entity comprises an irrigationsystem or a grain handling system.
 13. The system of claim 1, whereinthe one or more processors are configured to automatically track aparameter based on proximity of the first entity to the additionalentity.
 14. The system of claim 13, wherein the one or more processorsare configured to automatically track inventory usage based on proximityof the first entity to the additional entity, wherein the inventorycomprises at least one of fuel, seed, or a chemical.
 15. The system ofclaim 13, wherein the one or more processors are configured toautomatically track man hours based on proximity of the first entity tothe additional entity.
 16. The system of claim 1, wherein the spatialrelationship between the first entity and the additional entitycomprises a distance between the first communication device and theadditional communication device.
 17. The system of claim 1, wherein theidentifying a spatial relationship between the first entity and theadditional entity comprises determining a spatial relationship based onReceived Signal Strength (RSSI) values of at least one of one or moresignals from the first communication device or one or more signals fromthe additional communication device.
 18. The system of claim 1, whereinthe one or more signals from the first communication device and the oneor more signals from the additional communication device comprise globalpositioning system (GPS) positional data corresponding to at least oneof a geographical position of the first communication device or ageographical position of the additional communication device.
 19. Thesystem of claim 1, wherein the first communication device is configuredto collect data regarding one or more entity characteristics of thefirst entity, and the additional communication device is configured tocollect data regarding one or more entity characteristics of theadditional entity.
 20. The system of claim 19, wherein the one or moreentity characteristics of at least one of the first entity or theadditional entity comprise a fuel level.
 21. The system of claim 19,wherein the one or more entity characteristics of at least one of thefirst entity or the additional entity comprise a chemical level.
 22. Thesystem of claim 19, wherein the one or more entity characteristics of atleast one of the first entity or the additional entity comprise a seedlevel.
 23. A system comprising: a user interface; and a servercomprising a memory and one or more processors, wherein the one or moreprocessors are configured to: receive one or more signals from a firstcommunication device associated with a first entity; receive one or moresignals from at least an additional communication device associated withan additional entity; identify a spatial relationship between the firstentity and the additional entity based on one or more signals from thefirst communication device or one or more signals from the additionalcommunication device; identify an operation unit defined by anassociation between the first entity and the additional entity based onthe spatial relationship between the first entity and the additionalentity, wherein the operation unit comprises a combination of the firstentity and the additional entity, wherein the identification of theoperation unit is triggered by an identification of a distance, below athreshold distance, between the first communication device associatedwith the first entity and the additional communication device associatedwith the additional entity, wherein the first entity comprises a firstdevice and the additional entity comprises at least one of an additionaldevice or a person; determine whether the operation unit is positionedwithin a defined geo-fenced area; determine whether the operation unitis positioned within the defined geo-fenced area; determine one or morecharacteristics of the operation unit based on the determination of theoperation unit within the defined geo-fenced area; store the one or morecharacteristics of the operation unit in the database; and report theone or more characteristics of the operation unit via a user interface.24. A method comprising: associating a first communication device with afirst entity; associating an additional communication device with anadditional entity; identifying a spatial relationship between the firstentity and the additional entity based on one or more signals from thefirst communication device or one or more signals from the additionalcommunication device; identifying an operation unit defined by anassociation between the first entity and the additional entity based onthe spatial relationship between the first entity and the additionalentity, wherein the operation unit comprises a combination of the firstentity and the additional entity, wherein the identification of theoperation unit is triggered by an identification of a distance, below athreshold distance, between the first communication device associatedwith the first entity and the additional communication device associatedwith the additional entity, wherein the first entity comprises a firstdevice and the additional entity comprises at least one of an additionaldevice or a person; determining whether the operation unit is positionedwithin a defined geo-fenced area; determining one or morecharacteristics of the operation unit based on the determination of theoperation unit within the defined geo-fenced area; storing the one ormore characteristics of the operation unit in a database; and reportingthe one or more characteristics of the operation unit via a userinterface.